TECHNICAL FIELD
[001] The present subject matter is generally related to the field of industrial reactor (i.e., blast furnace reactor) for steel making process. Particularly, but not exclusively, the present disclosure relates to a method and a system for obtaining perpetual optimum performance of an industrial reactor.
BACKGROUND
[002] An industrial reactor (also, referred as blast furnace reactor) is a critical component in a multi-stage steel-making process chain. The performance of the entire steel-making process chain is dependent on the operation of the industrial reactor. For optimum operation of the industrial reactor, stability of the industrial reactor and quality of the product emanating from the industrial reactor are important. For instance, for stability of the industrial reactor, a fine balance is required between the composition of solid materials, the temperatures and pressures inside the industrial reactor, the oxygen-enriched hot air charged in at the bottom of the industrial reactor, counter flows of solids, liquids and gases inside the industrial reactor, and the liquid iron and slag tapped out at the bottom of the industrial reactor. If this balance is disturbed, it takes time for the industrial reactor to return to normal functioning, thereby, affecting the steel-making process chain. For quality of the product emanating from the industrial reactor, the product (i.e., liquid iron) temperature and its composition impact the downstream processing stages in the multi-stage steel-making process chain right up to the quality of the final product (i.e., steel) supplied to the user.
[003] Based on above-discussion, it is imperative that an industrial reactor always operates at the highest levels of (industrial reactor) stability and (product) quality. To achieve this objective an equilibrium has to be maintained, which is not easy. Moreover, there are external issues such as ambient humidity, ambient temperature, composition of raw materials and the like which influence the operation of the industrial reactor entailing shifts in the equilibrium.
[004] The information disclosed in this background of the disclosure section is for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

SUMMARY
[005] Additional features and advantages are realized through the techniques of the present disclosure. Other embodiments and aspects of the disclosure are described in detail herein and are considered a part of the claimed disclosure.
[006] There is a need for automatically controlling control state variables associated with an industrial reactor such that desired time-varying equilibrium between stability and quality is consistently maintained.
[007] Disclosed herein is a method for obtaining perpetual optimum performance of an industrial reactor. The method includes receiving a plurality of control state variables associated with the industrial reactor and determining variations of each of the plurality of control state variables against each of Key Objective Variables (KOVs). Thereafter, the method comprises discretizing the determined variations of each of the plurality of control state variables against each of the KOVs into a pre-determined number of intervals and determining a payoff value for the determined variations of each of the plurality of control state variable against each of the KOVs in each of the pre-determined number of intervals based on a relationship between each of the plurality of control state variables and the KOVs. The method comprises generating a payoff matrix for each of the KOVs using the payoff value determined in each of the pre-determined number of intervals for each of the plurality of control state variables. A total number of cells in the payoff matrix is based on the pre-determined number of intervals and a number of control state variables. Each cell of the payoff matrix comprises the payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix represents a control state variable. Subsequently, the method comprises determining weighted payoff matrix for each of the KOVs based on weight associated with respective KOVs and combining linearly the weighted payoff matrix of each of the KOVs to form a single payoff matrix. Lastly, the method comprises determining a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium using a Game Theory tool and controlling an operation of the industrial reactor using the determined payoff values of the control state variables to obtain perpetual optimum performance of the industrial reactor.

[008] Further, the present disclosure discloses a reactor operating system for obtaining perpetual optimum performance of an industrial reactor. The reactor operating system includes one or more processors and a memory communicatively coupled to the one or more processors, wherein the memory stores processor-executable instructions, which on execution, cause the one or more processors to receive a plurality of control state variables associated with the industrial reactor and to determine variations of each of the plurality of control state variables against each of Key Objective Variables (KOVs). Thereafter, the one or more processors is configured to discretize the determined variations of each of the plurality of control state variables against each of the KOVs into a pre-determined number of intervals. Subsequently, the one or more processors is configured to determine a payoff value for the determined variations of each of the plurality of control state variable against each of the KOVs in each of the pre-determined number of intervals based on a relationship between each of the plurality of control state variables and the KOVs. The one or more processors is configured to generate a payoff matrix for each of the KOVs using the payoff value determined in each of the pre¬determined number of intervals for each of the plurality of control state variables. A total number of cells in the payoff matrix is based on the pre-determined number of intervals and a number of control state variables. Each cell of the payoff matrix comprises the payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix represents a control state variable. Subsequently, the one or more processors is configured to determine weighted payoff matrix for each of the KOVs based on weight associated with respective KOVs and to combine linearly the weighted payoff matrix of each of the KOVs to form a single payoff matrix. Lastly, the one or more processors is configured to determine a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium using a Game Theory tool and to control an operation of the industrial reactor using the determined payoff values of the control state variables to obtain perpetual optimum performance of the industrial reactor.
[009] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS

[010] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described below, by way of example only, and with reference to the accompanying figures. The disclosure itself, however, as well as a preferred mode of use, further objectives, and advantages thereof, may best be understood by reference to the following detailed description of an illustrative embodiment when read in conjunction with the accompanying drawings. The novel features and characteristic of the disclosure are set forth in the appended claims.
[011] Figure 1a illustrates an exemplary environment for obtaining perpetual optimum performance of an industrial reactor in accordance with some embodiments of the present disclosure.
[012] Figure 1b illustrates data samples arranged in ascending order of one of the control state variables i.e., Cold Blast Flow Rate (CBFR) in Nm3/hr on X-axis against quality (i.e., hot metal Si wt. % in liquid iron indicating steel quality) on Y-axis in accordance with some embodiments of the present disclosure.
[013] Figure 1c illustrates data samples arranged in ascending order of one of the control state variables i.e., Oxygen Flow Rate (OFR) in Nm3/hr on X-axis against quality (i.e., hot metal Si wt. % in liquid iron indicating steel quality) on Y-axis in accordance with some embodiments of the present disclosure.
[014] Figure 1d illustrates payoff values of all control state variables in a two-dimensional matrix for the hot metal Si. %, where the first column in each column of matrix shows the payoff value of Oxygen Flow Rate (OFR) and second column in each column shows Cold Blast Humidity (CBH) in accordance with some embodiments of the present disclosure.
[015] Figure 2 shows a detailed block diagram of a reactor operating system in accordance with some embodiments of the present disclosure.

[016] Figure 3 illustrates a flowchart showing a method for obtaining perpetual optimum performance of an industrial reactor in accordance with some embodiments of present disclosure.
[017] Figure 4 illustrates a block diagram of an exemplary system for implementing embodiments consistent with the present disclosure.
[018] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flowcharts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.
DETAILED DESCRIPTION
[019] In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
[020] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.
[021] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.

[022] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
[023] The present disclosure discloses a method and a reactor operating system for obtaining perpetual optimum performance of an industrial reactor using Game Theory principle. Typically, the (non-cooperative) Game Theory principle is a framework where individual agents predict Nash Equilibrium using individual strategies of agents and payoffs.
[024] The concept of Game Theory principle is briefly discussed here. A Game is played between multiple agents. Every agent can be said to have three attributes. First, his/her belief (also, referred as understanding) of the world he/she lives in. This world is the limited sphere in which he/she operates, for example, for an agent in a stock-market, the world is the stock market. Second attribute includes his/her objectives (also, referred as desires), for instance, how he/her would like to change the states of this world. Third attribute includes his/her actions, for instance, the actions he/she takes to realize his/her objectives. There are multiple agents in the same world whose objectives are aligned differently and who concurrently take actions to shift the states of the world into conditions that are best suited to their objectives. That which constitutes the best action, an agent may take at any time for his/her best satisfaction, considering that every agent is, also, concurrently acting with correspondingly similar intent, form the Game Theory. All actions of an agent are explicitly defined, and the manner in which he/she would act under different conditions constitutes his/her strategy. Each action has a payoff or a numerically expressible reward (i.e., value) that depends, also, on the condition of the world and the actions of the other agents. Thus, each agent acts to maximize his/her payoff. Since this is true of every agent, there will be some point (also, referred as an action-vector) at which all agents receive their best payoff simultaneously. At other points (i.e., action vectors), the payoffs of some agents may increase while for other agents, the payoffs will decrease. Hence, the point (also, referred as action-vector) at which all agents receive their best payoff simultaneously constitutes or represents a Nash Equilibrium point of the Game

Theory. Using the Game Theory principle mentioned above, the method of the present disclosure controls or adjusts control state variables (acting as agents) associated with the industrial reactor to make the industrial reactor work continuously and consistently on the objective of stability of the industrial reactor and quality of steel. Each control state variable is treated as an agent and their interactions (acting as actions) are transformed through the framework of (non-cooperative) Game Theory principle into a mechanism to control of the industrial reactor that consistently ensures highest levels of stability and quality.
[025] The definitions of the terms used in the present disclosure are presented below:
[026] Key Objective Variables (KOVs): The objectives such as stability and quality are measured through KOVs. The KOVs refer to hot metal Silicon weight percentage (Si wt. %) in liquid iron indicating steel quality and resistance to permeability index indicating reactor stability.
[027] Payoff value: A payoff value with respect to each KOV represents a value that a control state variable attains by moving to a specific interval within the pre-determined number of intervals to achieve best KOV, which in turn represents objective. For example, quality (also, referred as steel quality) is an objective. Si wt. % is a measurable value – a KOV – that represents the objective quality. Analogously, stability (also, referred as reactor stability) is an objective. Resistance to permeability index is a measurable value – a KOV – that represents the objective stability.
[028] Payoff matrix: A payoff matrix refers to a matrix that comprises a total number of cells based on a pre-determined number of intervals and a number of control state variables, wherein each cell of the payoff matrix comprises a payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix represents a control state variable.
[029] Weighted payoff matrix: The weighted payoff matrix refers to a payoff matrix with weights. The weights are based on operational priorities of an industrial reactor for the steel making process.
[030] Matrix cell: The matrix cell refers to a cell containing payoff values of control state variables in a combined payoff matrix representing Nash Equilibrium.

[031] Nash Equilibrium: The Nash Equilibrium refers to a point (also, referred as action-vector) at which all agents receive their best payoff simultaneously in the Game Theory. In present disclosure, Nash Equilibrium refers to a point at which all control state variables (acting as agents) receive their best payoff value simultaneously to achieve a fine balance between stability and quality to obtain perpetual optimum performance of an industrial reactor.
[032] Figure 1a illustrates an exemplary environment for obtaining perpetual optimum performance of an industrial reactor in accordance with some embodiments of the present disclosure.
[033] As shown in the Figure 1a, the environment 100 includes a reactor operating system 101, a communication network 109, an industrial reactor 111 (also, referred as a blast furnace reactor) and a database 113. The operation of the industrial reactor 111 may be controlled by control state variables (also, referred as controllable process parameters) such as Cold Blast Flow Rate (CBFR), Cold Blast Humidity (CBH), Oxygen Flow Rate (OFR), Hot Blast Temperature (HBT), Coal Rate (CR) and Blast Furnace Gas (BFG). Each of these parameters are briefly explained below.
[034] CBFR: The CBFR refers to volumetric flow rate (measured in Nm3/hr) of atmospheric air pushed into the industrial reactor 111 through tuyeres (not shown in Figure 1a).
[035] CBH: The CBH refers to humidity of ambient atmosphere plus laterally injected steam flow (measured in g/Nm3 of dry CBFR). Atmospheric humidity cannot be controlled but the steam flow is controllable.
[036] OFR: The OFR refers to volumetric flow rate (measured in Nm3/hr) of oxygen that is pushed into the industrial reactor 111 through tuyeres.
[037] HBT: The HBT refers to temperature of the heated air (measured in °C) that is pushed into the tuyeres of the industrial reactor 111.
[038] CR: The CR refers to an amount of coal that is injected through tuyeres of the industrial reactor 111 in tons per hour basis.

[039] BFG: The BFG refers to a gas that emerges from the industrial reactor 111. This gas consists of Carbon monoxide (CO), Carbon dioxide (CO2), Nitrogen (N2) and Hydrogen (H2).
[040] The industrial reactor 111 may be communicatively coupled to the reactor operating system 101. The control state variables such as CBFR, CBH, OFR, HBT, CR and BFG collected from sensors (not shown in Figure 1a) attached to the industrial reactor 111 and/or calculated after collection from the sensors may be sent or transmitted to the reactor operating system 101 through the communication network 109. The communication network 109 may involve any of the following communication methods/protocols, but is not limited to, a direct interconnection, an e-commerce network, a Peer-to-Peer (P2P) network, Local Area Network (LAN), Wide Area Network (WAN), wireless network (for example, using Wireless Application Protocol), Internet, Wi-Fi, Bluetooth and the like.
[041] In the embodiment, the reactor operating system 101 may receive the control state variables such as CBFR, CBH, OFR, HBT, CR and BFG from sensors attached to the industrial reactor 111. Thereafter, the reactor operating system 101 may process the control state variables to control the operation of the industrial reactor 111 to obtain perpetual optimum performance of the industrial reactor 111. The processing of the control state variables to control the operation of the industrial reactor 111 using Game Theory principle is described in detail in later section. The reactor operating system 101 may include an I/O interface 103, a memory 105 and a processor 107, as shown in Figure 1a. The I/O interface 103 may be configured to receive the control state variables such as CBFR, CBH, OFR, HBT, CR and BFG from sensors attached to the industrial reactor 111. Analogously, the I/O interface 103 may be configured to communicate with a user interface (not shown in Figure 1a) to display the control state variables. In one embodiment, the I/O interface 103 may be configured to receive weight for each of Key Objective Variables (KOVs) as user inputs. The KOVs may comprise hot metal Silicon weight percentage (Si wt. %) in liquid iron indicating steel quality and resistance to permeability index (K) indicating (industrial) reactor stability.
[042] The control state variables received by the I/O interface 103 may be stored in the memory 105. The memory 105 may be communicatively coupled to the processor 107 of the reactor operating system 101. The memory 105 may, also, store processor instructions which

may cause the processor 107 to execute the instructions for obtaining perpetual optimum performance of the industrial reactor 111.
[043] The processor 107 may include at least one data processor for obtaining perpetual optimum performance of the industrial reactor 111. The processor 107 may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.
[044] The reactor operating system 101 may exchange data with the database 113. The database 113 may be populated or stored with at least one of a payoff matrix for each of the KOVs, a weighted payoff matrix for each of the KOVs and a combined payoff matrix. The payoff matrix comprises a total number of cells based on a pre-determined number of intervals and a number of control state variables, wherein each cell of the payoff matrix comprises a payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix represents a control state variable. A payoff value with respect to each KOV represents a value that a control state variable attains by moving to a specific interval within the pre¬determined number of intervals to achieve best KOV, which in turn represents objective. The database 113 may, also, be updated at a pre-set interval of time to account for process drift in the steel making process. These updates may be related to the payoff matrix for each of the KOVs, especially, updating payoff values present in the payoff matrix. The process drift may refer to unintended or unexpected drift of control state variables values away from its intended value in time ordered analysis. In general, process drift may be caused by any combination of three gradual occurrences or events – (a) mechanical wear and in case of blast furnace, it may be both wear as well as accumulation of hard material in some regions within the blast furnace (b) change in compositions and hence, properties of input materials and (c) experiments including changes in standard operation procedure or operating priorities by the operators of the blast furnace. Time duration for process drift may be considered from a month to a quarter. The pre-set interval of time may be every hour or every week or every month or every quarter or combination thereof.
[045] Hereafter, the operation of the reactor operating system 101 with respect to the industrial reactor 111 for obtaining perpetual optimum performance of the industrial reactor 111 using Game Theory principle is described.

[046] With reference to the Figure 1a, the reactor operating system 101 is communicatively coupled to the industrial reactor 111 for steel making process. The reactor operating system 101 receives a plurality of control state variables associated with the industrial reactor 111. The plurality of control state variables comprises Cold Blast Flow Rate (CBFR), Cold Blast Humidity (CBH), Oxygen Flow Rate (OFR), Hot Blast Temperature (HBT), Coal Rate (CR) and Blast Furnace Gas (BFG). In one embodiment, the plurality of control state variables received by the reactor operating system 101 may be pre-processed to filter (or remove) missing and abnormal values from the control state variables.
[047] At this stage, each of the plurality of control state variables such as CBFR, CBH, OFR, HBT, CR and BFG is considered as an individual agent (also, referred as an agent). The objectives of the agent (i.e., each of the plurality of control state variables) are defined as stability and quality. In one embodiment, stability and quality are considered as objectives of the agents (i.e., the plurality of control state variables). In this case, the actions of each agent (i.e., each of the plurality of control state variables) include to maximize each of the objectives i.e., stability and quality. The objectives such as stability and quality may be measured through Key Objective Variables (KOVs). For example, quality (also, referred as steel quality) is an objective. Si wt. % is a measurable value – a KOV – that represents the objective quality. Analogously, stability (also, referred as reactor stability) is an objective. Resistance to permeability index is a measurable value – a KOV – that represents the objective stability.
[048] In one embodiment, the KOVs comprise hot metal Silicon weight percentage in liquid iron (hereinafter, referred as hot metal Si wt. %) indicating steel quality and resistance to permeability index (K) indicating (industrial) reactor stability. For instance, the value of hot metal Si wt. % is a good indicator of quality. Lower Si implies better quality. When hot metal Si wt. % is below 0.7, quality index is 1; when hot metal Si wt. % is greater 1, the quality index is 0. Similarly, stability (also, referred as stability index) of the industrial reactor 111 varies inversely as resistance to permeability index (K). The permeability index (K) essentially reflects the ease of passage of gases from bottom to top of the industrial reactor 111. This is a physical stability. There is a second dimension to stability, which is called thermal stability. The thermal stability peaks at a certain range of the temperature of the liquid iron emanating from the bottom of the furnace and falls off thereafter. In the present disclosure, only stability from the physical stability represented resistance to permeability index (K) is considered. Thus,

the KOVs for quality and stability are hot metal Si wt. % and resistance to permeability index (K), respectively.
[049] The reactor operating system 101 determines variations of each of the plurality of control state variables against each of KOVs. Thereafter, the reactor operating system 101 discretizes the determined variations of each of the plurality of control state variables against each of the KOVs into a pre-determined number of intervals. For instance, each of the plurality of control state variables has an operational range. This operational range is discretized into a pre-determined number of intervals (also, referred as granules), which may be consistent for all the control state variables. An example is shown in Figure 1b. Figure 1b illustrates data samples arranged in ascending order of CBFR on X-axis against Si, wt. %, which is the KOV, on Y-axis. The variation is discretized into a pre-determined number of intervals, in this case, 7 intervals. The CBFR data samples are arranged on the X-axis in their ascending order. From Figure 1b, it is clear that most of the values (as seen in the level of variations) of CBFR are found in the upper 15% of their total range, while the lower half of the range has very few CBFR values. Statistically, the values of CBFR are concentrated only in the upper 15% of its total range. The rest of the values of CBFR are spread sparsely over 85% of its range on the lower side of its total range. In the upper 15% of its total range in Figure 1b, it is seen that the variation is mildly inverse i.e., Si, wt. % decreases with increasing CBFR. In the rest of the total range in Figure 1b, there is no noteworthy magnitude or direction of variation. Similarly, for quality (i.e., hot metal Si wt. %), the reactor operating system 101 determines variations of CBH, OFR, HBT, CR and BFG against hot metal Si wt. % and discretizes the determined variations of each of the CBH, OFR, HBT, CR and BFG against hot metal Si wt. % into a pre¬determined number of intervals (not shown in Figure 1b). Thereafter, the reactor operating system 101 determines variations of CBFR, CBH, OFR, HBT, CR and BFG against stability (i.e., resistance to permeability index (K)) and discretizes the determined variations of each of the CBFR, CBH, OFR, HBT, CR and BFG against resistance to permeability index (K) into a pre-determined number of intervals. Each control state variable is an agent, the variations of the control state variable against each of KOVs are discretized into a pre-determined number of intervals and the actions of the agent amount to shifting (or retaining) position from one interval to another interval.
[050] The reactor operating system 101 determines a payoff value for the determined variations of each of the plurality of control state variable against each of the KOVs in each of

the pre-determined number of intervals based on a relationship between each of the plurality of control state variables and the KOVs. The relationship between each of the plurality of control state variables and the KOVs is explained below.
[051] When a KOV is a hot metal Si wt. %, the reactor operating system 101 performs one of following operations:
[052] The reactor operating system 101 assigns a lowest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is highest value among the pre-determined number of intervals.
[053] The reactor operating system 101 assigns a highest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is lowest value among the pre-determined number of intervals.
[054] The reactor operating system 101 assigns an intermediate payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is between lowest and highest values among the pre-determined number of intervals, wherein the intermediate payoff value is a multiple of the lowest payoff value.
[055] When the KOV is a resistance to permeability index, the reactor operating system 101 performs one of following operations:
[056] The reactor operating system 101 assigns lowest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is highest value among the pre-determined number of intervals.
[057] The reactor operating system 101 assigns highest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the

resistance to permeability index in the interval is lowest value among the pre-determined number of intervals.
[058] The reactor operating system 101 assigns an intermediate payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is between lowest and highest values among the pre-determined number of intervals. The intermediate payoff value is a multiple of the lowest payoff value.
[059] A payoff value with respect to each KOV represents a value that a control state variable attains by moving to a specific interval within the pre-determined number of intervals to achieve best KOV. For instance, with reference to Figure 1b, the KOV on the Y-axis is hot metal Si wt. %, which varies inversely with respect to the KOV it represents, namely quality. So, the intervals of CBFR that have high average (within the interval) values of hot metal Si. wt. % map into low payoff values, and the intervals of CBFR that have low average (within the interval) values of hot metal Si. wt. % map into high payoff values. In order to assign a number to the payoff value, the method of the present disclosure requires a constant baseline number for each of the plurality of control state variables and each of KOVs. For example, the baseline number is considered as 14 and multiples of 14 are used to represent proportionately increasing payoff values. With reference to Figure 1b, the reactor operating system 101 assigns a lowest payoff value i.e., 14 to first interval among the pre-determined number of intervals i.e., 7 for CBFR with respect to the hot metal Si wt. % when an average value of the hot metal Si wt. % in the interval is highest value among the pre-determined number of intervals. Similarly, the reactor operating system 101 assigns a highest payoff value 98 (i.e., 14x7) to last interval among the pre-determined number of intervals i.e., 7 for CBFR with respect to the hot metal Si wt. % when an average value of the hot metal Si wt. % in the interval is lowest value among the pre-determined number of intervals. Thereafter, the reactor operating system 101 assigns an intermediate payoff value (i.e., between 14 to 98, which are 28 (14x2), 42 (14x3), 56 (14x4), 70 (14x5), 84 (14x6)) to an interval (other than first and last intervals) among the pre-determined number of intervals i.e., 7 for CBFR with respect to the hot metal Si wt. % when an average value of the hot metal Si wt. % in the interval is between lowest and highest values among the pre-determined number of intervals. The intermediate payoff value is a multiple of the lowest payoff value, in this example, multiple of 14. With reference to Figure 1b, the lowest payoff value i.e., value 14 for CBFR with respect to the hot metal Si wt. % is in

its first interval, and the highest payoff i.e., value 98 (i.e., 14x7) for CBFR with respect to the hot metal Si wt. % is in its last interval i.e., interval 7. Another example is shown in Figure 1c, which illustrates hot metal Si wt. % versus OFR. The 7 payoff values determined by the reactor operating system 101 are 14 for interval 1, 28 for interval 2, 56 for interval 3, 98 for interval 4, 84 for interval 5, 70 for interval 6 and 42 for interval 7.
[060] Subsequently, the reactor operating system 101 generates a payoff matrix for each of the KOVs using the payoff value determined in each of the pre-determined number of intervals for each of the plurality of control state variables. A total number of cells in the payoff matrix is based on the pre-determined number of intervals and a number of control state variables. Each cell of the payoff matrix comprises the payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix represents a control state variable. For instance, KOVs such hot metal Si wt. % relating to quality and resistance to permeability index (K) relating to stability are considered for which a separate payoff matrix is generated by the reactor operating system 101. For a given KOV, there are 6 control state variables that contribute to payoff matrix, namely CBFR, OFR, CBH, HBT, CR and BFG. Each control state variable is discretized into 7 intervals. For example, if there are “n” control state variables, and “m” pre-determined number of intervals, then the total number of dimensions of the payoff matrix will be n, and each dimension split (i.e., rows, columns, pages, etc.) into m pre¬determined number of intervals. The total number of cells in the payoff matrix is based on the pre-determined number of intervals and a number of control state variables will be mn, which in this case is 76. Each cell of the payoff matrix comprises the payoff value of each of the plurality of control state variables i.e., each cell has 6 payoff values wherein each payoff value represents a value that indicates how well objective (quality or stability) is served when 6 control state variables are positioned in the middle value of the interval represented by that cell of the payoff matrix. In the six-dimensional matrix, each cell represents one interval from each of the six dimensions, which in turn implies a vector of actions (i.e., a payoff value) taken by each of the six agents (i.e., control state variables), leading to a six-dimensioned tuple of payoff values.
[061] For ease of understanding, this is explained first with respect to a two-dimensional matrix, and thereafter more dimensions can be added easily by addition. Let the variables in the two dimensions be referred as var1 (for row) and var2 (column), and assuming each variable i.e., var 1 and var 2 are both discretized into 7 intervals. Now, there are 7 payoff values

designated as {p11, p21, …, p71} for each of 7 intervals of var1, and {p21, p22, …, p27} for each of 7 intervals of var2. These payoff values have been extracted by the reactor operating system 101 by observation of the variations of the relevant KOV with respect to two control state variables represented by var1 and var2. Here, there is no information on how {p11, p21, …, p71} vary with var2 (i.e., the second or column subscript), and how {p11, p12, …., p17} vary with var1 (i.e., first or row subscript). This implies that in the two-dimensional payoff matrix, the first vector (i.e., payoff value) will remain unchanged across the columns, while the second vector (i.e., payoff value) will remain fixed across the rows. For a two-dimensional tuple of payoff values in each cell of this matrix, the first number will remain fixed across columns, and the second will not change across rows. Extending the above discussion to higher dimensions, in a three-dimensional matrix, the third vector (i.e., payoff values) will vary across the pages (planes) but remain fixed for any page. The first dimension varies only across rows, the second dimension varies only across columns, and the third dimension varies only across the pages. This discussion is extended to six dimensions and the variations within the 6-tuple of numbers in each cell. This is illustrated in Figure 1d showing the two-dimensional view of each matrix. Figure 1d shows the payoff values of all control state variables in a two-dimensional matrix for the hot metal Si. %, where the first column in each column of matrix shows the payoff value of OFR and second column in each column shows CBH. Subsequently, rest of the columns represents the rest of the four control state variables. Figure 1d represents the construction of a payoff matrix for a single KOV i.e., hot metal Si wt. %. So, in total, there will be two identically dimensioned matrices one for each of the KOVs i.e., hot metal Si wt. % and resistance to permeability index (K).
[062] The reactor operating system 101 receives weight for each of the KOVs as user inputs based on operational priorities of the industrial reactor 111 for the steel making process. These weights reflect the relative importance of the objectives at the time of operation. The user inputs are received through the user interface (not shown in Figure 1) communicatively coupled to the I/O interface 103 of the reactor operating system 101. Thereafter, the reactor operating system 101 determines weighted payoff matrix for each of the KOVs based on weight associated with respective KOVs and combines linearly the weighted payoff matrix of each of the KOVs to form a single payoff matrix. For instance, the operational priorities of the industrial reactor 111 vary across time periods. The operational priorities are influenced by the priorities of the steel-making process chain for that particular period. Sometimes the throughput of the industrial reactor 111 is to be maximized, at other times the quality of steel is found to

have digressed and needs to be improved, or there are too many fluctuations, as a result stability of the industrial reactor 111 needs to be increased. In present disclosure, there are two payoff matrices i.e., one for hot metal Si wt. % and one for resistance to permeability index (K), each of six dimensions, identically structured with 76 numbers of cells. Only the internal 6-tuples in identically positioned cells are different. So, based on the operational priorities for steel quality i.e., hot metal Si wt. % and stability i.e., resistance to permeability index (K) at a period, weights are allocated to the two payoff matrices which are linearly combined across every single cell’s tuples to create a combined payoff matrix with identical structure. In detail, this is done by linearly adding two matrices after giving a constant weight to each matrix, where the matrices are of six dimensions. This new matrix of six dimensions is used for the Game Theory execution to attain or identify a matrix cell corresponding to Nash Equilibrium.
[063] The reactor operating system 101 determines a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium using a Game Theory tool. The Game Theory tool is a Gambit analytical tool. As the operational priorities change, the weights for each of the KOVs change. Every such change entails a new search for the Nash Equilibrium. For example, when the operational priority of the industrial reactor 111 is to maintain balance between the two KOVs i.e., hot metal Si wt. % indicating quality and resistance to permeability index (K) indicating stability, equal weight, say 0.5, is assigned to each of the two KOVs. These weights reflect the relative importance of the objectives at the time of operation. As a result, the reactor operating system 101 determines a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium. The matrix cell containing payoff values of control state variables is given as:
[064] {OFR, CBH, CBFR, HBT, CR, BFG-CO} → {4, 1, 5, 7, 4, 5}
[065] The above payoff values imply that OFR settles in interval 4 and CBH settles in interval 1. Similarly, rest four control state variables settle in intervals 5, 7, 4 and 5 respectively to attain the Nash Equilibrium for this the operational priority.
[066] When the operational priority of the industrial reactor 111 is to maintain higher hot metal Si wt. % indicating quality and lower resistance to permeability index (K) indicating stability, then hot metal Si wt. % in liquid iron is assigned higher weight, say 0.8 and resistance

to permeability index (K) is assigned lower weight, say 0.2. These weights reflect the relative importance of the objectives at the time of operation. As a result, the reactor operating system 101 determines a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium. The matrix cell containing payoff values of control state variables is given as
[067] {OFR, CBH, CBFR, HBT, CR, BFG-CO} → {4, 1, 5, 7, 5, 6}
[068] The above payoff values imply that OFR settles in interval 4 and CBH settles in interval 1. Similarly, rest four control state variables settle in intervals 5, 7, 5 and 6 respectively to attain the Nash Equilibrium for this the operational priority.
[069] Subsequently, the reactor operating system 101 controls the operation of the industrial reactor 111 using the determined payoff values of the control state variables to obtain perpetual optimum performance of the industrial reactor 111. As Nash Equilibrium changes with change in operational priorities, the reactor operating system 101 controls the operation of the industrial reactor 111 such that the reactor operating system 101 obtains optimum performance of the industrial reactor 111 continuously.
[070] Figure 2 shows a detailed block diagram of a reactor operating system in accordance with some embodiments of the present disclosure.
[071] The reactor operating system 101, in addition to the I/O interface 103 and processor 107 described above, may include data 201 and one or more modules 221, which are described herein in detail. As an example, the data 201 and the modules 221 may be stored within the memory 105 configured in the reactor operating system 101. The data 201 may include, for example, Cold Blast Flow Rate data 203, Cold Blast Humidity data 205, Oxygen Flow Rate data 207, Hot Blast Temperature data 209, Coal Rate data 211, Blast Furnace Gas data 213 and other data 215.
[072] The Cold Blast Flow Rate data 203 relates to the Cold Blast Flow Rate (CBFR) control state variable. The CBFR of the industrial reactor 111 received by the reactor operating system 101 is stored as the Cold Blast Flow Rate data 203.

[073] The Cold Blast Humidity data 205 relates to the Cold Blast Humidity (CBH) control state variable. The CBH of the industrial reactor 111 received by the reactor operating system 101 is stored as the Cold Blast Humidity data 205.
[074] The Oxygen Flow Rate data 207 relates to the Oxygen Flow Rate (OFR) control state variable. The OFR of the industrial reactor 111 received by the reactor operating system 101 is stored as the Oxygen Flow Rate data 207.
[075] The Hot Blast Temperature data 209 relates to the Hot Blast Temperature (HBT) control state variable. The HBT of the industrial reactor 111 received by the reactor operating system 101 is stored as the Hot Blast Temperature data 209.
[076] The Coal Rate data 211 relates to the Coal Rate (CR) control state variable. The CR of the industrial reactor 111 received by the reactor operating system 101 is stored as the Coal Rate data 211.
[077] The Blast Furnace Gas data 213 relates to the Blast Furnace Gas (BFG) control state variable. The BFG of the industrial reactor 111 received by the reactor operating system 101 is stored as the Blast Furnace Gas data 213.
[078] The other data 215 may store data, including temporary data and temporary files, generated by one or more modules 221 for performing the various functions of the reactor operating system 101.
[079] In some embodiments, the data 201 stored in the memory 105 are processed by the one or more modules 221 of the reactor operating system 101. The one or more modules 221 may be stored within the memory 105. As an example, the one or more modules 221 communicatively coupled to the processor 107 configured in the reactor operating system 101, may also be present outside the memory 105. In some implementations, the one or more modules 221 may be communicatively coupled to the processor 107 for performing one or more functions of the reactor operating system 101. The said modules 221 when configured with the functionality defined in the present disclosure will result in a novel hardware.

[080] In one implementation, the one or more modules 221 may include, but are not limited to, a receiving module 223, a determining module 225, a generating module 227, a combining module 229, a controlling module 231 and an updating module 233. The one or more modules 221 may, also, include other modules 235 to perform various miscellaneous functionalities of the reactor operating system 101.
[081] The receiving module 223 of the reactor operating system 101 may receive a plurality of control state variables associated with the industrial reactor 111. The plurality of control state variables may comprise of CBFR, CBH, OFR, HBT, CR and BFG. The receiving module 223 may receive the plurality of control state variables through the I/O interface 103 of the reactor operating system 101. In this case, the receiving module 223 may send the received plurality of control state variables to the determining module 225.
[082] Furthermore, the receiving module 223 of the reactor operating system 101 may receive the weight for each of the KOVs as user inputs based on operational priorities of the industrial reactor 111 for the steel making process. The weight for each of the KOVs may be based on operational priorities of the industrial reactor 111 for the steel making process. In this case, the receiving module 223 may send the received weight for each of the KOVs to the determining module 225.
[083] The determining module 225 of the reactor operating system 101 may determine variations of each of the plurality of control state variables against each of KOVs. The KOVs may comprise hot metal Si wt. % indicating steel quality and resistance to permeability index indicating (industrial) reactor stability. Thereafter, the determining module 225 of the reactor operating system 101 may discretize the determined variations of each of the plurality of control state variables against each of the KOVs into a pre-determined number of intervals. Subsequently, the determining module 225 of the reactor operating system 101 may determine a payoff value for the determined variations of each of the plurality of control state variable against each of the KOVs in each of the pre-determined number of intervals based on a relationship between each of the plurality of control state variables and the KOVs. For instance, when a KOV is a hot metal Si wt. %, the determining module 225 of the reactor operating system 101 may perform one of following operations:

[084] The determining module 225 may assign a lowest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is highest value among the pre-determined number of intervals.
[085] The determining module 225 may assign a highest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is lowest value among the pre-determined number of intervals.
[086] The determining module 225 may assign an intermediate payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is between lowest and highest values among the pre-determined number of intervals. The intermediate payoff value may be a multiple of the lowest payoff value.
[087] When the KOV is a resistance to permeability index, the determining module 225 of the reactor operating system 101 may perform one of following operations:
[088] The determining module 225 may assign a lowest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is highest value among the pre-determined number of intervals.
[089] The determining module 225 may assign a highest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is lowest value among the pre-determined number of intervals.
[090] The determining module 225 may assign an intermediate payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is between lowest and highest values among the pre-determined number of intervals. The intermediate payoff value may be a multiple of the lowest payoff value.

[091] Furthermore, the determining module 225 of the reactor operating system 101 may determine weighted payoff matrix for each of the KOVs based on weight associated with respective KOVs when a payoff matrix is received from the generating module 227.
[092] When the determining module 225 of the reactor operating system 101 receives the single payoff matrix (also, referred as the combined payoff matrix) from the combining module 229, the determining module 225 may determine a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium using a Game Theory tool. The Game Theory tool may be a Gambit analytical tool.
[093] The generating module 227 of the reactor operating system 101 may generate a payoff matrix for each of the KOVs using the payoff value determined in each of the pre-determined number of intervals for each of the plurality of control state variables. A total number of cells in the payoff matrix may be based on the pre-determined number of intervals and a number of control state variables. Each cell of the payoff matrix may comprise the payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix may represent a control state variable.
[094] The combining module 229 of the reactor operating system 101 may combine linearly the weighted payoff matrix of each of the KOVs to form a single payoff matrix. The combining module 229 may send its output i.e., the single payoff matrix (also, referred as the combined payoff matrix) to the determining module 225 for determining a matrix cell representing Nash Equilibrium.
[095] The controlling module 231 of the reactor operating system 101 may control the operation of the industrial reactor 111 using the determined payoff values of the control state variables received from the determining module 225 to obtain perpetual optimum performance of the industrial reactor 111.
[096] The updating module 233 of the reactor operating system 101 update the payoff values present in the payoff matrix at a pre-set interval of time to account for process drift in the steel making process in the industrial reactor 111. The updates may be received or collected from the sensors attached to the industrial reactor 111. Furthermore, the updating module 233 may,

also, update the database 113 at a pre-set interval of time to account for process drift in the steel making process. These updates may be related to the payoff matrix for each of the KOVs, especially, updating payoff values present in the payoff matrix.
[097] Figure 3 illustrates a flowchart showing a method for obtaining perpetual optimum performance of an industrial reactor in accordance with some embodiments of present disclosure.
[098] As illustrated in Figure 3, the method 300 includes one or more blocks for obtaining perpetual optimum performance of an industrial reactor 111. The method 300 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions or implement particular abstract data types.
[099] The order in which the method 300 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.
[100] At block 301, the reactor operating system 101 associated with the industrial reactor 111 for steel making process may receive a plurality of control state variables associated with the industrial reactor 111. The plurality of control state variables may comprise Cold Blast Flow Rate (CBFR), Cold Blast Humidity (CBH), Oxygen Flow Rate (OFR), Hot Blast Temperature (HBT), Coal Rate (CR) and Blast Furnace Gas (BFG).
[101] At block 303, the reactor operating system 101 may determine variations of each of the plurality of control state variables against each of Key Objective Variables (KOVs). The KOVs may comprise hot metal Silicon weight percentage (Si wt. %) in liquid iron indicating steel quality and resistance to permeability index indicating reactor stability.

[102] At block 305, the reactor operating system 101 may discretize the determined variations of each of the plurality of control state variables against each of the KOVs into a pre-determined number of intervals.
[103] At block 307, the reactor operating system 101 may determine a payoff value for the determined variations of each of the plurality of control state variable against each of the KOVs in each of the pre-determined number of intervals based on a relationship between each of the plurality of control state variables and the KOVs.
[104] At block 309, the reactor operating system 101 may generate a payoff matrix for each of the KOVs using the payoff value determined in each of the pre-determined number of intervals for each of the plurality of control state variables. A total number of cells in the payoff matrix may be based on the pre-determined number of intervals and a number of control state variables. Each cell of the payoff matrix may comprise the payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix may represent a control state variable.
[105] At block 311, the reactor operating system 101 may determine weighted payoff matrix for each of the KOVs based on weight associated with respective KOVs. The weight for each of the KOVs may be based on operational priorities of the industrial reactor 111 for the steel making process.
[106] At block 313, the reactor operating system 101 may combine linearly the weighted payoff matrix of each of the KOVs to form a single payoff matrix.
[107] At block 315, the reactor operating system 101 may determine a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium using a Game Theory tool. The Game Theory tool may be a Gambit analytical tool.
[108] At block 317, the reactor operating system 101 may control an operation of the industrial reactor 111 using the determined payoff values of the control state variables to obtain perpetual optimum performance of the industrial reactor 111.

[109] Some of the technical advantages of the present disclosure are listed below.
[110] The present disclosure automatically facilitates the industrial reactor 111 to operate, perpetually, at the level, which is best for all the objectives of the industrial reactor 111 in an integral manner. The reactor operating system 101 disclosed in the present disclosure is an advanced control system that bypasses tables and charts used by operators of the industrial reactor 111 to set different control variables at specific levels under specific conditions.
[111] As performance of the entire steelmaking process chain is dependent crucially on the performance of the industrial reactor 111 (also, referred as blast furnace), it is imperative that the industrial reactor 111 always operates at the highest levels of stability and quality. Hence, an equilibrium has to be maintained between stability and quality for a correct operational balance of the industrial reactor 111. The method and the reactor operating system of the present disclosure achieve the above-mentioned objective.
[112] The reactor operating system 101 and the method of the present disclosure uses Game Theory principle to perform complex operations on control state variables to achieve a fine balance (i.e., Nash Equilibrium) between stability and quality to obtain optimum performance of the industrial reactor 111 continuously.
[113] Figure 4 illustrates a block diagram of an exemplary system for implementing embodiments consistent with the present disclosure.
[114] In an embodiment, the system 400 may be used to implement the reactor operating system 101. The system 400 may include a central processing unit (“CPU” or “processor”) 402. The processor 402 may include at least one data processor for obtaining perpetual optimum performance of an industrial reactor 111. The processor 402 may include specialized processing units such as, integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.
[115] The processor 402 may be disposed in communication with one or more input/output (I/O) devices (not shown in Figure 4) via I/O interface 401. The I/O interface 401 employ communication protocols/methods such as, without limitation, audio, analog, digital, monoaural, Radio Corporation of America (RCA) connector, stereo, IEEE-1394 high speed

serial bus, serial bus, Universal Serial Bus (USB), infrared, Personal System/2 (PS/2) port, Bayonet Neill-Concelman (BNC) connector, coaxial, component, composite, Digital Visual Interface (DVI), High-Definition Multimedia Interface (HDMI), Radio Frequency (RF) antennas, S-Video, Video Graphics Array (VGA), IEEE 802.11b/g/n/x, Bluetooth, cellular e.g., Code-Division Multiple Access (CDMA), High-Speed Packet Access (HSPA+), Global System for Mobile communications (GSM), Long-Term Evolution (LTE), Worldwide interoperability for Microwave access (WiMax), or the like, etc.
[116] Using the I/O interface 401, the system 400 may communicate with one or more I/O devices such as input devices 412 and output devices 413. For example, the input devices 412 may be an antenna, keyboard, mouse, joystick, (infrared) remote control, camera, card reader, fax machine, dongle, biometric reader, microphone, touch screen, touchpad, trackball, stylus, scanner, storage device, transceiver, video device/source, etc. The output devices 413 may be a printer, fax machine, video display (e.g., Cathode Ray Tube (CRT), Liquid Crystal Display (LCD), Light-Emitting Diode (LED), plasma, Plasma Display Panel (PDP), Organic Light-Emitting Diode display (OLED) or the like), audio speaker, etc.
[117] In some embodiments, the system 400 consists of the reactor operating system 101. The processor 402 may be disposed in communication with the communication network 409 via a network interface 403. The network interface 403 may communicate with the communication network 409. The network interface 403 may employ connection protocols including, without limitation, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), Transmission Control Protocol/Internet Protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc. Using the network interface 403 and the communication network 409, the system 400 may communicate with the industrial reactor 111 and the database 113.
[118] The communication network 409 includes, but is not limited to, a direct interconnection, a Peer to Peer (P2P) network, Local Area Network (LAN), Wide Area Network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, Wi-Fi and such.
[119] In some embodiments, the processor 402 may be disposed in communication with a memory 405 (e.g., RAM, ROM, etc. not shown in Figure 4) via a storage interface 404. The storage interface 404 may connect to memory 405 including, without limitation, memory drives, removable disc drives, etc., employing connection protocols such as, Serial Advanced

Technology Attachment (SATA), Integrated Drive Electronics (IDE), IEEE-1394, Universal Serial Bus (USB), fiber channel, Small Computer Systems Interface (SCSI), etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc.
[120] The memory 405 may store a collection of program or database components, including, without limitation, user interface 406, an operating system 407, etc. In some embodiments, the system 400 may store user/application data, such as, the data, variables, records, etc., as described in this disclosure. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as Oracle or Sybase.
[121] The operating system 407 may facilitate resource management and operation of the system 400. Examples of operating systems include, without limitation, APPLE® MACINTOSH® OS X®, UNIX®, UNIX-like system distributions (E.G., BERKELEY SOFTWARE DISTRIBUTION® (BSD), FREEBSD®, NETBSD®, OPENBSD, etc.), LINUX® DISTRIBUTIONS (E.G., RED HAT®, UBUNTU®, KUBUNTU®, etc.), IBM®OS/2®,
MICROSOFT® WINDOWS® (XP®, VISTA®/7/8, 10 etc.), APPLE® IOS®, GOOGLETM ANDROIDTM, BLACKBERRY® OS, or the like.
[122] In some embodiments, the system 400 may implement web browser 408 stored program components. Web browser 408 may be a hypertext viewing application, such as MICROSOFT® INTERNET EXPLORER®, GOOGLETM CHROMETM, MOZILLA® FIREFOX®, APPLE® SAFARI®, etc. Secure web browsing may be provided using Secure Hypertext Transport Protocol (HTTPS), Secure Sockets Layer (SSL), Transport Layer Security (TLS), etc. Web browsers 408 may utilize facilities such as AJAX, DHTML, ADOBE® FLASH®, JAVASCRIPT®, JAVA®, Application Programming Interfaces (APIs), etc. The system 400 may implement a mail server (not shown in Figure 4) stored program component. The mail server may be an Internet mail server such as Microsoft Exchange, or the like. The mail server may utilize facilities such as ASP, ACTIVEX®, ANSI® C++/C#, MICROSOFT®, .NET, CGI SCRIPTS, JAVA®, JAVASCRIPT®, PERL®, PHP, PYTHON®, WEBOBJECTS®, etc. The mail server may utilize communication protocols such as Internet Message Access Protocol (IMAP), Messaging Application Programming Interface (MAPI), MICROSOFT® exchange, Post Office Protocol (POP), Simple Mail Transfer Protocol (SMTP), or the like. The system 400

may implement a mail client (not shown in Figure 4) stored program component. The mail client may be a mail viewing application, such as APPLE® MAIL, MICROSOFT® ENTOURAGE®, MICROSOFT® OUTLOOK®, MOZILLA® THUNDERBIRD®, etc.
[123] Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include Random Access Memory (RAM), Read-Only Memory (ROM), volatile memory, non-volatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.
[124] The described operations may be implemented as a method, system or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof. The described operations may be implemented as code maintained in a “non-transitory computer readable medium”, where a processor may read and execute the code from the computer readable medium. The processor is at least one of a microprocessor and a processor capable of processing and executing the queries. A non-transitory computer readable medium may include media such as magnetic storage medium (e.g., hard disk drives, floppy disks, tape, etc.), optical storage (CD-ROMs, DVDs, optical disks, etc.), volatile and non-volatile memory devices (e.g., EEPROMs, ROMs, PROMs, RAMs, DRAMs, SRAMs, Flash Memory, firmware, programmable logic, etc.), etc. Further, non-transitory computer-readable media include all computer-readable media except for a transitory. The code implementing the described operations may further be implemented in hardware logic (e.g., an integrated circuit chip, Programmable Gate Array (PGA), Application Specific Integrated Circuit (ASIC), etc.).
[125] The terms “an embodiment”, “embodiment”, “embodiments”, “the embodiment”, “the embodiments”, “one or more embodiments”, “some embodiments”, and “one embodiment” mean “one or more (but not all) embodiments of the invention(s)” unless expressly specified otherwise.

[126] The terms “including”, “comprising”, “having” and variations thereof mean “including but not limited to”, unless expressly specified otherwise.
[127] The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise.
[128] The terms “a”, “an” and “the” mean “one or more”, unless expressly specified otherwise.
[129] A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.
[130] When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.
[131] The illustrated operations of Figure 3 show certain events occurring in a certain order. In alternative embodiments, certain operations may be performed in a different order, modified, or removed. Moreover, steps may be added to the above-described logic and still conform to the described embodiments. Further, operations described herein may occur sequentially or certain operations may be processed in parallel. Yet further, operations may be performed by a single processing unit or by distributed processing units.
[132] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention

be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.
[133] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope being indicated by the following claims.

REFERRAL NUMERALS:

Reference number Description
100 Environment
101 Reactor operating system
103 I/O Interface
105 Memory
107 Processor
109 Communication network
111 Industrial reactor
113 Database
201 Data
203 Cold blast flow rate data
205 Cold blast humidity data
207 Oxygen flow rate data
209 Hot blast temperature data
211 Coal rate data
213 Blast furnace gas data
215 Other data
221 Modules
223 Receiving module
225 Determining module
227 Generating module
229 Combining module
231 Controlling module
233 Updating module
235 Other modules
400 System
401 I/O interface
402 Processor
403 Network interface
32

404 Storage interface
405 Memory
406 User interface
407 Operating system
408 Web browser
409 Communication network
412 Input devices
413 Output devices
33

We claim:
1. A method for obtaining perpetual optimum performance of an industrial reactor, the
method comprising:
receiving, by a reactor operating system associated with the industrial reactor for steel making process, a plurality of control state variables associated with the industrial reactor;
determining, by the reactor operating system, variations of each of the plurality of control state variables against each of Key Objective Variables (KOVs);
discretizing, by the reactor operating system, the determined variations of each of the plurality of control state variables against each of the KOVs into a pre-determined number of intervals;
determining, by the reactor operating system, a payoff value for the determined variations of each of the plurality of control state variable against each of the KOVs in each of the pre-determined number of intervals based on a relationship between each of the plurality of control state variables and the KOVs;
generating, by the reactor operating system, a payoff matrix for each of the KOVs using the payoff value determined in each of the pre-determined number of intervals for each of the plurality of control state variables, wherein a total number of cells in the payoff matrix is based on the pre-determined number of intervals and a number of control state variables, each cell of the payoff matrix comprises the payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix represents a control state variable;
determining, by the reactor operating system, weighted payoff matrix for each of the KOVs based on weight associated with respective KOVs;
combining linearly, by the reactor operating system, the weighted payoff matrix of each of the KOVs to form a single payoff matrix;
determining, by the reactor operating system, a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium using a Game Theory tool; and
controlling, by the reactor operating system, an operation of the industrial reactor using the determined payoff values of the control state variables to obtain perpetual optimum performance of the industrial reactor.

2. The method as claimed in claim 1, wherein the plurality of control state variables comprises Cold Blast Flow Rate (CBFR), Cold Blast Humidity (CBH), Oxygen Flow Rate (OFR), Hot Blast Temperature (HBT), Coal Rate (CR) and Blast Furnace Gas (BFG).
3. The method as claimed in claim 1, wherein the KOVs comprise hot metal Silicon weight percentage (Si wt. %) in liquid iron indicating steel quality and resistance to permeability index indicating reactor stability.
4. The method as claimed in claim 1, wherein the relationship between each of the plurality of control state variables and the KOVs comprises:
when a KOV is a hot metal Si wt. %, performing one of:
assigning, by the reactor operating system, a lowest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is highest value among the pre-determined number of intervals; or
assigning, by the reactor operating system, a highest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is lowest value among the pre-determined number of intervals; or
assigning, by the reactor operating system, an intermediate payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is between lowest and highest values among the pre-determined number of intervals, wherein the intermediate payoff value is a multiple of the lowest payoff value.
5. The method as claimed in claim 4 further comprises:
when the KOV is a resistance to permeability index, performing one of:
assigning, by the reactor operating system, a lowest payoff value to an interval
among the pre-determined number of intervals for the control state variable when an
average value of the resistance to permeability index in the interval is highest value
among the pre-determined number of intervals; or
assigning, by the reactor operating system, a highest payoff value to an interval
among the pre-determined number of intervals for the control state variable when an

average value of the resistance to permeability index in the interval is lowest value among the pre-determined number of intervals; or
assigning, by the reactor operating system, an intermediate payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is between lowest and highest values among the pre-determined number of intervals, wherein the intermediate payoff value is a multiple of the lowest payoff value.
6. The method as claimed in claim 1, comprising:
receiving, by the reactor operating system, the weight for each of the KOVs as user inputs based on operational priorities of the industrial reactor for the steel making process.
7. The method as claimed in claim 1, wherein the Game Theory tool is a Gambit analytical tool.
8. The method as claimed in claim 1, further comprising:
updating, by the reactor operating system, the payoff values present in the payoff matrix at a pre-set interval of time to account for process drift in the steel making process.
9. The method as claimed in claim 1, wherein the weight for each of the KOVs is based on operational priorities of the industrial reactor for the steel making process.
10. A reactor operating system for obtaining perpetual optimum performance of an industrial reactor, the reactor operating system comprising:
one or more processors;
a memory communicatively coupled to the one or more processors, wherein the memory stores processor instructions, which, on execution, causes the one or more processors to:
receive a plurality of control state variables associated with the industrial reactor;
determine variations of each of the plurality of control state variables against each of Key Objective Variables (KOVs);
discretize the determined variations of each of the plurality of control state variables against each of the KOVs into a pre-determined number of intervals;

determine a payoff value for the determined variations of each of the plurality of control state variable against each of the KOVs in each of the pre-determined number of intervals based on a relationship between each of the plurality of control state variables and the KOVs;
generate a payoff matrix for each of the KOVs using the payoff value determined in each of the pre-determined number of intervals for each of the plurality of control state variables, wherein a total number of cells in the payoff matrix is based on the pre-determined number of intervals and a number of control state variables, each cell of the payoff matrix comprises the payoff value of each of the plurality of control state variables, and each dimension of the payoff matrix represents a control state variable;
determine weighted payoff matrix for each of the KOVs based on weight associated with respective KOVs;
combine linearly the weighted payoff matrix of each of the KOVs to form a single payoff matrix;
determine a matrix cell containing payoff values of control state variables in the combined payoff matrix representing Nash Equilibrium using a Game Theory tool; and
control an operation of the industrial reactor using the determined payoff values of the control state variables to obtain perpetual optimum performance of the industrial reactor.
11. The reactor operating system as claimed in claim 10, wherein the plurality of control state variables comprises Cold Blast Flow Rate (CBFR), Cold Blast Humidity (CBH), Oxygen Flow Rate (OFR), Hot Blast Temperature (HBT), Coal Rate (CR) and Blast Furnace Gas (BFG).
12. The reactor operating system as claimed in claim 10, wherein the KOVs comprise hot metal Silicon weight percentage (Si wt. %) in liquid iron indicating steel quality and resistance to permeability index indicating reactor stability.
13. The reactor operating system as claimed in claim 10 is configured to:
when a KOV is a hot metal Si wt. %, perform one of:

assigning a lowest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is highest value among the pre-determined number of intervals; or
assigning a highest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is lowest value among the pre-determined number of intervals; or
assigning an intermediate payoff value to an interval among the pre¬determined number of intervals for the control state variable when an average value of the hot metal Si wt. % in the interval is between lowest and highest values among the pre-determined number of intervals, wherein the intermediate payoff value is a multiple of the lowest payoff value.
14. The reactor operating system as claimed in claim 13 is configured to:
when the KOV is a resistance to permeability index, perform one of:
assigning a lowest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is highest value among the pre-determined number of intervals; or
assigning a highest payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is lowest value among the pre-determined number of intervals; or
assigning an intermediate payoff value to an interval among the pre-determined number of intervals for the control state variable when an average value of the resistance to permeability index in the interval is between lowest and highest values among the pre-determined number of intervals, wherein the intermediate payoff value is a multiple of the lowest payoff value.
15. The reactor operating system as claimed in claim 10 is configured to:
receive the weight for each of the KOVs as user inputs based on operational priorities of the industrial reactor for the steel making process.

16. The reactor operating system as claimed in claim 10, wherein the Game Theory tool is a Gambit analytical tool.
17. The reactor operating system as claimed in claim 10 is configured to:
update the payoff values present in the payoff matrix at a pre-set interval of time to account for process drift in the steel making process.
18. The reactor operating system as claimed in claim 10, wherein the weight for each of the
KOVs is based on operational priorities of the industrial reactor for the steel making process.