BACKGROUND
The subject matter disclosed herein relates to turbomachinery, and more particularly, to tuning control systems for gas turbines.
In power generation systems, turbines, such as gas turbines or steam turbines, may convert fuel and air (e.g., an oxidant) into rotational energy. For example, a gas turbine may compress the air, via a compressor, and mix the compressed air with the fuel to form an air-fuel mixture. A combustor of the gas turbine may then combust the air-fuel mixture and use energy from the combustion process to rotate one or more turbine blades, thereby generating rotational energy. The rotational energy may then be converted into electricity, via a generator, to be provided to a power grid, a vehicle, or another load.
Various sub-systems of the gas turbine may be controlled using a proportional-integral (PI) controller, a proportional-derivative (PD) controller, or a proportional-integral-derivate (PID) controller to achieve specific operating conditions.
BRIEF DESCRIPTION
Certain embodiments commensurate in scope with the originally claimed disclosure are summarized below. These embodiments are not intended to limit the scope of the claimed disclosure, but rather these embodiments are intended only to provide a brief summary of possible forms of the disclosure. Indeed, embodiments may encompass a variety of forms that may be similar to or different from the embodiments set forth below.
In a first embodiment, a computing device includes a display, one or more processors, and memory storing instructions. The instructions cause the one or more processors to receive an indication of a process of industrial machinery to be tuned to cause an actuator of the industrial machinery to change, thereby causing perturbation of operating parameter of the industrial machinery. Furthermore, the instructions cause the one or more processors to receive response data indicative of a response of the industrial machinery to the perturbation of operation of the
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industrial machinery. Further, the instructions cause the one or more processors to determine one or more controller parameters based at least in part on the response data, display the one or more controller parameters via the display, and cause the one or more controller parameters to be pushed to a controller of the industrial machinery.
In a second embodiment, a tangible, non-transitory, and computer-readable medium having instructions stored that, when executed by a processor of an edge device of industrial machinery that couples a controller of a plant to outside devices, cause the one or more processors to collect system response data to a perturbation of operation of a plant. Further, the processor sends the system response data indicative of system response of the plant to a computing device and a cloud service. Moreover, the processor calculates controller parameters based on one or more target system response parameters, receives a validation from the computing device, where the validation is an indication of approval of the controller parameters; and push the controller parameters to a controller on the plant.
In a third embodiment, an industrial machinery system includes industrial machinery including a controller, an edge device coupled to the controller, and a computing device. The edge device includes a processor and memory storing instructions that cause the processor to receive an indication of a perturbation to at least one operating parameter of the industrial machinery from the computing device. Further, the instructions cause the processor to collect response data indicative of the response of the industrial machinery to the perturbation from the controller, determine one or more controller parameters based at least in part on the response of the industrial machinery relative to the target response, and push the one or more controller parameters to the controller.
BRIEF DESCRIPTION OF THE DRAWINGS
These and other features, aspects, and advantages of the present disclosure will become better understood when the following detailed description is read with
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reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:
FIG. 1 is a block diagram of a gas turbine system and a controller that controls one or more operating parameters of the gas turbine, in accordance with an embodiment;
FIG. 2 is a block diagram of an architecture arrangement that enables control of a plant using a computing device and an edge device, in accordance with an embodiment;
FIG. 3 is a flow diagram of a process performed by the computing device, in accordance with an embodiment; and
FIG. 4 is a flow diagram of a process performed by the edge device, in accordance with an embodiment.
DETAILED DESCRIPTION
One or more specific embodiments of the present disclosure will be described below. In an effort to provide a concise description of these embodiments, all features of an actual implementation may not be described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers’ specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.
When introducing elements of various embodiments of the present disclosure, the articles “a,” “an,” “the,” and “said” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements.
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Embodiments of the present disclosure are related to control systems for industrial machinery, such as gas turbines, steam turbines, and/or compressors. For example, industrial machinery containing a gas turbine may include one or more compressors, a combustor, and one or more turbine blades. The gas turbine may receive an oxidant, such as air, in the one or more compressors that compress the air to a higher pressure. The air is mixed with fuel to form an air-fuel mixture that is combusted by the combustor. Energy from the combustion process is used to rotate turbine blades of the one or more turbines. The rotational energy of the turbine blades may rotate a shaft coupled to the turbine blades to drive one or more loads, such as a vehicle or an electrical generator. The electrical generator may be coupled to a power grid to provide power that is used for residential, industrial, or any other suitable purpose.
Gas turbines may include control systems that control one or more operations of the gas turbine. For example, a control system of a gas turbine may control the exhaust temperature of the gas turbine by modulating the inlet guide vanes, control the compressor operating limit by modulating the inlet bleed valves, control the emissions by modulating the gas control valves, or the like The control system may include one or more controllers, such as a proportional-integral-derivative (PID) controller, a proportional-integral (PI) controller, a proportional-derivative (PD) controller, that control one or more operations of the gas turbine by determining a difference (e.g., error) between a reference signal (e.g., received as the target response) and a feedback signal (e.g., received from sensors). As an example, the PID controller may reduce the difference over time by adjusting an output signal from the PID controller based on a proportional gain, an integral gain, and a derivative gain of the PID controller. For instance, the controller may control the exit temperature of the combustor by comparing a reference signal of a target exit temperature to feedback from a temperature sensor or a model of the combustor exit temperature.
The gains of the PI, PD, and/or PID controller, hereinafter called “controller” (e.g., to reference either a PI, PD, or PID controller) may be predetermined offline
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based on one or more factors that are estimated from the known design of the components (e.g., compressor, combustor, turbine blades) of the gas turbine. However, it may enhance the adaptability of the controller to various scenarios if the gains of the controller may be updated remotely or on site with the aid of a computing device, an edge device, a cloud service including one or more servers or any combination thereof that may be used to collectively calculate controller parameters (e.g., the controller gains, controller structure, etc.). The computing device may be any wireless and/or wired computing device such as a cellular device, a tablet, a laptop, and/or any other suitable wireless device communicatively couple to the edge device. The edge device is an external, stand-alone device comprising non-transitory, computer-readable medium configured to cause a processor to execute instructions stored in the memory to perform functions such as calculating parameters (e.g., controller gains), receiving commands from a computing device, sending signals indicative of controller parameters to the plant and/or other suitable functions. In some embodiments, the edge device may include an edge server that may communicate with external devices, store data (e.g., algorithms) that may be used to calculate parameters, etc.
Keeping the foregoing in mind, embodiments of the present disclosure describe systems and methods that account for tuning controllers remotely to cause a change in a parameter, hereinafter called “operating parameters,” of a component of industrial machinery by adjusting the controller parameters via a computing device. Hereinafter, when referencing a component of industrial machinery, “plant” may be used to describe the said component. The industrial machinery, such as a gas turbine system, may include a computing device (e.g., cellular device, laptop, tablet, etc.) and an edge device of a power plant communicatively coupled to the controller, whereby the gains of the controller may be tuned (e.g., modified) and may cause the industrial machinery to achieve a target response. The edge device may be connected to one or more networks of industrial machinery and may serve as a gateway device for the industrial machinery to devices outside the one or more networks of the industrial machinery. The edge device may also serve as a centralized location for obtaining response data
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indicative of a response of the industrial machinery. The response data may, in turn, be used to obtain a mathematical transfer function relating inputs to outputs based on the response data received as empirical data. While temperature and pressure may be used as examples of operating parameters below, controllers of gas turbines may control any suitable operating parameter of the gas turbine.
The computing device may then request an input (e.g., perturbation) into the plant, such as a gas turbine system, to perturb the operation of the gas turbine system. The input may cause one or more subcomponents of the gas turbine system to be perturbed, thereby changing their respective operating parameters, in some instances. For example, the computing device may insert a step input to the gas control valve position of the gas turbine system. That is, the computing device may perturb the gas turbine system (e.g., or any subcomponent of the gas turbine system), thereby altering an operating parameter, in some instances. Then the edge device may receive response data indicative of the perturbation response. For example, the edge device may then determine a transfer function (e.g., s-domain input/output relationship) based on the perturbation and the corresponding response. The transfer function may characterize an output of part of the gas turbine with respect to the input (e.g. step input) of the gas turbine. For example, the transfer function may characterize the pressure variations within the combustor from an acoustic sensor inside the combustor with respect to a signal that opens or closes a fuel valve to controls flow of fuel entering a fuel nozzle into the combustor. The edge device may then determine gains (e.g., controller parameters) from that particular operating point based at least on the aforementioned transfer function and response data to achieve a target performance criteria (e.g., predetermined stability margin) based on inputs from a computing device or predetermined criteria stored in a cloud service. Furthermore, in some embodiments, many loop tuning algorithms may be stored in the cloud service, wherein the cloud service may be modified by a remote-control center. While the cloud service is discussed in detail below, it should be noted that in certain embodiments the cloud service may be absent from the embodiments and the embodiments may still accomplish the disclosed subject
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matter. That is, while the cloud service may enhance the performance of the disclosed subject matter, in certain embodiments, the cloud service may be omitted.
Turning now to the drawings, FIG. 1 illustrates a block diagram of an embodiment of a gas turbine system 10. The diagram includes fuel nozzles 12, a fuel supply 14, and a combustor 16. As depicted, the fuel supply 14 routes a liquid fuel and/or gas fuel, such as natural gas or syngas, to the turbine system 10 through the fuel nozzle 12 and into the combustor 16. The combustor 16 ignites and combusts the fuel-air mixture, and then passes hot pressurized combustion gases 17 (e.g., exhaust) into a turbine 18. Turbine blades may be coupled to a shaft 19, which is also coupled to several other components throughout the turbine system 10, as illustrated. As the combustion gases 17 pass through the turbine blades in the turbine 18, the turbine 18 is driven into rotation, which also causes the shaft 19 to rotate. Eventually, the combustion gas 17 may exit the turbine system 10 via an exhaust outlet 20.
In an embodiment of the turbine system 10, compressor blades may be included as components of the compressor 22. The blades within the compressor 22 may be coupled to the shaft 19, and may turn as the shaft 19 is driven to rotate by the turbine 18, as discussed above. The compressor 22 may intake air to the turbine system 10 via an air intake 24. Further, the shaft 19 may be coupled to a load 26, which may be powered via rotation of the shaft 19. By way of example, the load 26 may be any suitable device that may generate power via the rotational output of the turbine system 10, such as a power generation plant or an external mechanical load. For instance, the load 26 may include an electrical generator, a propeller of an airplane, and so forth. The air intake 24 draws air 30 into the turbine system 10 via a suitable mechanism, such as a cold air intake, for subsequent mixture of the air 30 with the fuel supply 14 via the fuel nozzle 12. The air 30 taken in by the turbine system 10 may be fed and compressed into pressurized air by rotating blades within the compressor 22. The pressurized air, shown by reference number 32, may then be fed into the fuel nozzle 12. The fuel
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nozzle 12 may then mix the pressurized air and fuel, shown by reference number 34, to produce a suitable mixture ratio for combustion, e.g., a combustion that causes the fuel to more completely burn, so as not to waste fuel or cause excess emissions.
The turbine system 10 also includes one or more sensors 35 to acquire measurements associated with operation of the turbine system 10. The illustrated sensors 35 are coupled to the fuel nozzle 12, combustor 16, the turbine 18, and compressor 22. In certain embodiments where the turbine system 10 is a component of, for example, a power plant, the exhaust outlet 20 may be coupled to a heat recovery steam generator (HRSG) to recover heat from the exhaust to generate steam for use in various applications such as a steam turbine, which in turn may be coupled to an exhaust stack. The exhaust stack may redirect the HRSG’s exhaust gases into the atmosphere. Accordingly, the sensors 35 may also be coupled to the various power plant components, such as the HRSG and the exhaust stack.
The sensors 35 may obtain various measurements regarding fluid, temperature, pressure, and the like. That is, certain sensors 35 may be used to measure properties of a gas, a gas-liquid mixture, or a liquid. For example, certain embodiments may monitor a gas flow from the combustor 16 to detect various emissions, temperature, pressure, flow rate, fluctuations in time, variations in space, and so forth. Other sensor 35 embodiments may monitor, for example, a gas flow through the turbine 18 to detect blade anomalies, rotational efficiency, and so forth. The sensor 35 embodiments may also obtain various emission measurements. For example, the sensor 35 coupled to the compressor 22 may be an acoustic to measure compressor blade inlet heat, temperature, and/or pressure. It is noted that while compressor inlet pressure is described in detail below, any suitable measurement(s) may be monitored by the sensors 35 in accordance with embodiments described herein.
The turbine system 10 may include one or more actuators 37 (e.g., valves) that control operating parameters of the turbine system 10. In the illustrated
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embodiment, the turbine system 10 includes a premix fuel valve that controls flow of fuel entering the fuel nozzle 12. It is noted that while the premix fuel valve is described in detail below, any suitable actuator(s)/control(s) may be used to control operation of the gas turbine system 10 in accordance with embodiments described herein.
A controller 40 may be electrically coupled to one or more of the sensors 35 to receive signals indicating one or more operating parameters of the gas turbine system 10. The controller 40 may include a processor 42 that executes instructions that may be stored in memory 44. The processor 42 may include any suitable processor such as a microprocessor, application-specific integrated circuit (ASIC), field-programmable gate arrays (FPGA) and/or any other suitable processor for performing actions indicated in the instructions. The memory 44 may be any tangible, non-transitory, and computer-readable medium, such as read-only memory (ROM), randomly accessible memory (RAM), flash memory, optical drives, magnetic hard drives, and/or any other suitable memory types.
The controller 40 may receive a signal from the sensor 35 coupled to the compressor 22 indicating inlet temperature or heat of air 30. Further, the controller 40 is electrically coupled to the one or more actuators 37 to send signals to control one or more operating parameters of the gas turbine system 10. For example, the controller 40 may send a signal to the actuator 37 coupled to the fuel nozzle 12 to control flow of the fuel entering the fuel nozzle 12.
The controller 40 may control various operations of the gas turbine system 10 using data received from the sensors 35. For example, the controller 40, such as a proportional-integral-derivative (PID) controller, may control one or more operations of the gas turbine system 10 by determining a difference (e.g., error) between a reference signal, indicating a target operation of the gas turbine system 10, and a feedback signal of one or more measurements from the sensors 35. While a PID controller is described herein, this may include any combination of proportional, integral, and derivative gains (e.g. as described above) suitable for controlling the target operation of the gas turbine system 10. The controller 40
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may reduce the difference over time by adjusting an output signal from the controller 40 to the actuator 37 based on a proportional gain, an integral gain, a derivative gain, or a combination thereof, of the controller 40. For instance, the controller 40 may control the inlet pressure of the combustor 16 by controlling opening or closing of a fuel valve of the fuel nozzle 12 based on a difference between a reference signal of a target inlet pressure compared to feedback from a temperature sensor or a model of the combustor exit temperature.
The proportional gain may be a term that is proportional to the difference between the reference signal and the feedback signal of the gas turbine. The integral gain may be a term that is proportional to a sum of the difference in error over a period of time. The derivative gain may be a term that is proportional to the rate of change of the difference. The controller 40 may control the operating parameter based on controller gains (e.g., terms) that are calculated offline by an edge device 70 based on the various components (e.g., combustor, compressor, and turbine blades) of the gas turbine achieving suitable plant characteristics (e.g., rise time, settling time, closed loop bandwidth, etc.). Further, the edge device may receive data indicative of the response of the plant to a perturbation that may be initiated by a computing device. The edge serve may adjust the gains of the controller to reduce the difference between the reference signal and the feedback signal of the plant while maintaining stability of the system, thereby improving efficiency of the plant (e.g., the gas turbine). For example, the gains may be lowered to increase response time but decrease likelihood of overcompensation in driving the industrial machinery.
FIG. 2 is a block diagram of an architecture arrangement that enables control of a plant 50 using a computing device 60 and/or an edge device 70. The edge device 70 may receive input signals from the computing device 60 or a cloud service 80. The cloud service 80 includes one or more servers 81 that are computing devices including processors and memory similar to those previously discussed in reference to the controller 40. The cloud service 80 may be modified and/or updated by a remote control center 82 in addition or alternative to the computing
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device 60 and/or the edge device 70. The plant 50 includes sensors 35, actuators 37, and controller 40. The computing device 60 includes processor 62 and memory 64 similar to those previously discussed in reference to the controller 40. The edge device 70 includes processor 72 and memory 74 similar to those previously discussed in reference to the controller 40. While such architecture arrangement illustrated in FIG. 2 is described with respect to the control the gas turbine components described above with regards to FIG. 1, it should be appreciated that in some embodiments, the systems and methods mentioned above and below may be incorporated into other plants.
The controller 40 may receive information, via sensors 35, related to the plant 50, which may include the intake valve, the compressor 22, the fuel nozzle 12, the combustor 16, the turbine blades, and other suitable component of the industrial machinery. For example, control of the plant 50 may refer to the control of the inlet temperature of the compressor 22 (e.g., the temperature at the compressor inlet 22) by the actuation of the actuator 37 such as an inlet bleed heat valve.
The computing device 60 may receive inputs from an input mechanism (e.g., a keystroke or touch gesture from a plant operator at the site). For example, the computing device 60 may receive an indication of a process of the industrial machinery to be tuned to cause an operating parameter of the industrial machinery to change (e.g., or be perturbed), thereby causing a perturbation of the operation of the industrial machinery and its components, where the industrial machinery and its components may be any plant 50. For example, the computing device 60 may receive a command (e.g., via a button configuration, screen touch interface, etc.) from the plant operator indicative of a step signal, which is then sent to the edge device 70 for further processing. Once received by the edge device 70, the step signal (e.g. signal indicative of the perturbation) is sent to the plant 50 to accordingly perturb the plant. The edge device 70 identifies the response of the plant 50 to the step signal. The response may include plant characteristics (e.g., rise time, settling time, etc.) and a signal indicative of the plant response and plant
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characteristics is sent to the computing device 60. As such, the computing device 60 is communicatively coupled to the edge device 70.
The edge device 70 may be communicatively coupled to the sensors 35, the plant 50, the computing device 60, and the cloud service 80 via a wireless and/or wired connection. In more detail, the edge device 70 may collect and store data indicative of the characteristics of the plant 50 (e.g., as raw data from the sensors 35 or processed via the controller 40 or the cloud service 80), couple a controller 40 of the plant 50 to outside devices, receive an indication of a perturbation to be cause or that has been cause to the plant 50, send system response data to the computing device 60 of the plant’s response to the perturbation, and receive data at a specified sampling rate (e.g. from sensors 35). In certain embodiments, the data may be stored in the cloud service 80 and/or processed by the edge device 70 (e.g., to determine suitable controller parameters). In some embodiments, the edge device may store the algorithms to determine the plant transfer function or determine the controller parameters (e.g., controller gains, etc.).
In some embodiments, the cloud service 80, may store plant-tuning algorithms (e.g., instructions for calculating controller parameters corresponding to specified plant characteristics), wherein the algorithms specify computer-readable instructions that may be sent to and/or executed by the edge device 70. For example, the plant operator may send an input to the computing device 60 specifying certain plant characteristics (e.g., a quick settling time for the inlet temperature of the gas turbine). In certain embodiments, the edge device 70 may search through the cloud service 80 (or local memory) to identify an algorithm with instructions specifying controller gains that have previously been utilized to achieve the specific plant characteristics (e.g., a quick settling time for the inlet temperature of the gas turbine) corresponding to a specific response of the plant 50. If already stored in the cloud service 80 (e.g., or memory 74), the controller gains corresponding to the plant 50 may be used. The cloud service 80 may be updated via a remote control center 82.
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In addition, the remote control center 82 may be used to analyze data (e.g., real-time data from the edge device 70 via the cloud service 80, etc.), and help further tune the control parameters calculated by the edge device 70. In some embodiments, the remote control center 82 or the computing device 60 may serve as a quality checkpoint to ensure that the controller parameters calculated by the edge device 70 are suitable. In certain embodiments, the plant operator may and/or technician in the remote control center 82 send a validation signal (e.g., push an approve button) via the computing device 60 and/or remote control center 82, when the plant operator approves of the controller gains calculated by the edge device 70. In further embodiments, the operators of the remote control center 82 may also send validation signals to the cloud service 80, indicating approval of the controller parameters outputted by the edge device 70 to the controller 40. In further embodiments, a priority scheme may be used, wherein the validation signal of the remote control center 82 may override the validation signal of the computing device 60. For example, if the edge device 70 receives a validation signal from the remote control center 82, but receives a signal from the computing device 60 disapproving of the control parameters, the control parameters would still be pushed to (e.g., incorporated into) controller 40. Alternatively, a priority scheme may be utilized, wherein the validation from the computing device 60 may override the validation from the remote control center 82.
FIG. 3 is a flow diagram 100 of a process performed by the computing device. More specifically, the process blocks that make up flow diagram 100 illustrate, instructions stored in memory, wherein the instructions are configured to cause the processor of the computing device to receive an indication of a perturbation request (block 102), send the requested perturbation to the edge device 70 (block 104), determine the controller parameters (block 106), display the controller parameters (block 108), and push the controller parameters to a controller (block 110).
The computing device 60 receives an indication of a perturbation request (block 102). In certain embodiments, the indication of the perturbation may come from a
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plant operator. The indication of the perturbation may be in the form of an electric signal processed by the computing device 60. The computing device 60 may receive an indication of the perturbation via inputs into the computing device 60 (e.g., via a touch screen interface, a button configuration, etc.) by the plant operator, such that the indication of the perturbation indicates a process to be tuned. For example, the plant operator may operate an inlet bleed heat valve (e.g., or any other plant 50) to control the compressor inlet temperature (e.g., or any other operating parameter) of the compressor 22 of a gas turbine system. The plant operator may press buttons on the button configuration of the computing device 60, sending a signal to perturb the compressor 22. The signal may input a step function and/or cause a step function related to a selected process to be tuned. The step function perturbs the inlet bleed valve resulting in compressor inlet temperature to respond 22. In this example, the plant perturbed is the inlet bleed heat system 22, and the boundary perturbed is the inlet temperature of the compressor 22. However, it should be noted that the flow diagram 100 is applicable to any plant receiving any perturbation that perturbs any operating parameter/boundary.
Upon receiving the indication of the perturbation (block 102), the computing device 60 sends the requested perturbation to the edge device 70 (block 104). The perturbation is any change to an operating parameter of the plant. As mentioned above, the computing device 60 and the edge device 70 may be communicatively coupled via a wireless network connection such as a Personal Area Network (PAN) connection, Local Area Network (LAN) connection, Wide Area Network (WAN) connection, or any other suitable wireless network communication.
Upon sending the requested perturbation to the edge device 70 (block 104), in certain embodiments, the edge device 70 may perturb the plant 50 and determine the plant response to the perturbation. In further embodiments, after the edge device 70 determines/measures the plant response, the edge device may then determine the plant model and resulting controller parameters (block 106). That is, the edge device 70 may receive response data (e.g., sensor data of the plant 50
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from the edge device 70 indicative of the response of the plant 50 to the perturbation). The processor 72 of the edge device 70 may then determine the controller parameters (block 106) based at least in part on the data (e.g., response data) received from the plant 50.
To continue the aforementioned example, once the indication of the impulse/step response of the inlet temperature of the compressor 22 (e.g., which serves as the plant 50 in this example) is sent to the edge device 70 by the computing device 60, the computing device 60 may receive response data from the edge device 70. In some embodiments, the plant operator may then specify on the edge device 70 through the computing device 60 that the closed loop (e.g., transient) response should have a minimum overshoot (e.g., which serves as the target plant characteristic in this example). The processor 72 of the edge device 70 may determine the controller gains (e.g., which serve as the controller parameters in this example) of the controller actuating the inlet bleed heat valve (e.g., which serves as the actuator in this example) to cause the inlet temperature (e.g., which serves as the operating parameter in this example) of the compressor to have a minimum overshoot. In certain embodiments, the computing device 60 may use parallel computing and/or the edge device 70 to determine the controller parameters.
The determined controller parameters are displayed on the computing device 70 (block 108). The computing device 60 includes a display, which may include a liquid crystal display (LCD), an electroluminescent display (ELD), a cathode ray tube display (CRT), and/or a light emitting diode (LED) display among many other display options for relaying information to a plant operator. The controller parameters displayed by the computing device 60 may include the gains (e.g., proportional, integral, or derivative gains), the controller structure (e.g., whether the controller is a PI, PD, or PID controller), controller transfer function, a simulation of the closed loop response using the new gains, open loop step response, and/or any suitable controller parameters. To build further on the aforementioned example, the controller parameters associated with causing the
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temperature of the inlet bleed heat valve to have a minimum overshoot may be displayed on the LCD screen of the computing device 60.
In further embodiments, along with displaying the controller parameters, the computing device 60 may display the plant characteristics, such as the rise time, settling time, max overshoot value, closed-loop response, closed-loop transfer function, close loop bandwidth, a simulation of the plant response, and/or other suitable controller parameters that may aid a plant operator in validating the overall effectiveness of the determined controller parameters. To build further on the aforementioned example, the plant characteristics associated with the response of the compressor inlet temperature having a minimum overshoot may be displayed on the LCD screen of the computing device 60.
After receiving a display of the controller parameters, in some embodiments, an operator may send a confirmation to push the controller parameters to the controller. Afterwards, the computing device may push the control parameters to a controller (block 110). That is, the instructions stored in the memory of the computing device 60 are configured to cause the processor(s) 62 of the computing device 60 to request a confirmation of the results as valid before pushing the controller parameters to the plant 50. As such, a plant operator may validate the controller parameters displayed on the computing device 60, push (e.g., push a series of buttons), and therefore, implement the controller parameters on the controller.
For example, upon receiving a display of the response (e.g., via a simulation using new gains based on plant characteristics derived from response to the perturbation) of the compressor’s inlet temperature response, and after verifying that the overshoot meets the response criteria (e.g., a minimum overshoot response), then the plant operator may press a button reading “Confirm” on the button configuration of the computing device 60. Pressing the “Confirm” button may push the controller parameters to the controller controlling the inlet bleed heat valve, which in turn controls the inlet temperature of the compressor 22. In some embodiments, the edge device 70 may push the gains to the controller 40
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automatically. However, in certain embodiments, these gains may be used only temporarily until approval has been obtained. For example, the gains may be used for some period (e.g., 1 hour) without approval. If the gains are not approved during that time, the controller 40 may revert to previous gains until the new gains are approved.
In some embodiments, after pushing (e.g., implementing) the controller parameters, using the computing device, the plant operator may choose to perform a closed loop test on the plant. That is, the plant operator may send a request to perturb the reference signal and view the closed loop response on the computing device. For example, with regards to the above mentioned control of the compressor inlet temperature, after implementing the controller parameters, the plant operator may request to send a step function to the closed loop system. After sending the request, the operator may view the closed loop response for the compressor inlet temperature.
FIG. 4 is a flow diagram 120 of a process performed by the edge device 70. More specifically, the process blocks comprising flow diagram 100, illustrate instructions stored in memory, wherein the instructions are configured to cause the processor of the edge device 70 to receive an indication of a requested perturbation from a computing device 60 (block 122), collect system response data from the plant 50 (block 124), send system response data to the computing device 60 (block 126), calculate controller parameters (block 128), receive a validation (block 130), and push the controller parameters to controller 40 (block 132).
The edge device 70 receives an indication of the requested perturbation (block 122). In certain embodiments, this indication of the requested perturbation may come from the computing device 60. The indication of the requested perturbation received by the edge device 70 may be in the form of an electric signal and/or any indication of a tuning from the mobile device 60 that the processor 72 of the edge device 70 processes. The perturbation may be a unit impulse function, a unit step function, or any suitable perturbation to an operating parameter of a plant 50. For
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example, the edge device 70 may receive a signal from the computing device 60 indicating a request to perturb the inlet temperature of the compressor 22 with an input step function. As a result, in certain embodiments, the edge device 70 may accordingly perturb the compressor (e.g., plant 50). While in this example, the compressor 22 serves as the plant 50, the inlet temperature serves as the operating parameter, and the input unit step function serves as the perturbation, it should be noted that the above and below mention subject matter is applicable to any plants, operating parameters, and/or perturbations.
Flow diagram 120, indicates that the edge device 70 collects system response data (block 124). The system response data may include response data (e.g., real-time data obtained via sensors) of the plant 50 subject to the perturbation, response data of the plants 50 and operating parameters affected by the perturbation, and/or any other suitable response data resulting at least in part due to the perturbation. In certain embodiments, collecting the system response data may include perturbing the plant 50 accordingly, and receiving data (e.g., via sensors) indicative of the perturbation.
The edge device 70 then sends system response data (block 126) to any of the components it is in communication with (e.g., computing device 60, the cloud service 80, and/or the plant 50). That is, the edge device 70 may send the system response data (e.g., via a wireless network, etc.) to the cloud service 80 for further analysis by a remote control center 82. Furthermore, the edge device 70 may send the system response data (e.g., via a wireless network, etc.) to the computing device 60 for further analysis by a plant operator.
In some embodiments, the edge device 70 may await the criteria of plant characteristics requested by the computing device 60. For example, after the edge device 70 sends the system response data indicative of a response to the step function of the inlet temperature of the compressor 22 to the computing device 60, the computing device 60 may specify the criteria of plant characteristics. For example, in some embodiments, the operator of the computing device 60 may
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specify that the inlet temperature response of the compressor must have a settling time of less than five seconds.
Accordingly, the edge device 70 calculates controller parameters (block 128) upon receiving the criteria of plant characteristics to according tune the plant 50. In certain embodiments, the criteria of plant characteristics may be sent by the computing device 60 and the cloud service 80. The controller parameters may be determined based at least in part on the response (e.g., real-time response) of the plant 50 relative to the target response. The target response may be a system response for an operating parameter of a plant 50, whereas the response may be the real-time response obtained from sensors on the plant 50. Furthermore, in certain embodiments, a priority scheme may be implemented wherein a first device (e.g., the computing device 60) has priority over a second device (e.g., the cloud service 80), such that the criteria of the first device may override the criteria of the second device. The processor 72 of the edge device 70 may take a criteria of the plant characteristics, and then calculate the controller parameters. The controller parameters calculated may include the types of controller gains (e.g., proportional gain, integral gain, derivative gain, etc.), the values of the controller gains, the structure of the controller (e.g., PID controller, PI controller, PD controller, etc.), and/or any other suitable controller parameters. These controller parameters may be sent to the cloud service 80 for further analysis and/or sent to the computing device 60 to await a validation.
In certain embodiments, once the computing device 60 may specify the criteria of plant characteristics, the edge device 70 may receive the criteria, which may indicate that the response of the plant 50 (e.g., compressor 22) should have a settling time of less than five seconds. In certain embodiments, the control parameters are calculated by the edge device 70, as described above. In further embodiments, the controller parameters may be calculated by the computing device 60. After the controller parameters are computed, the edge device 70 sends the controller parameters and/or the plant characteristics to the computing device 60 to await a validation.
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In more detail, the edge device 70 receives a validation (block 130) from the computing device 60 and/or the cloud service 80 once the controller parameters have been approved by the plant operator and/or the remote access center 82. Again, a priority scheme may be set up, wherein the validation from a first device (e.g., the computing device 60) may override the validation or lack of from a second device (e.g., the cloud service 80). As mentioned above, in certain embodiments, the validation received by the edge device 70 may be an electric signal wirelessly communicated from the computing device 60. In further embodiments, the processor 72 of the edge device 70 may not press (e.g., incorporate) the controller parameters into the controller 40 of the plant 50 until a validation has been received.
As such, upon receiving a validation from either the computing device 60 and/or cloud service 80, the edge device 70 pushes the controller parameters to controller 40 (block 132) of the plant 50. After receiving the validation, the controller parameters (e.g., controller gains, PID controller configuration, etc.) may be incorporated into operation by the controller of the plant 50. To continue the example above, if the controller parameters indicative of a five second settling time for the temperature of the compressor 22 calculated by the edge device 70 are approved by the computing device 60 (e.g., or the user of the computing device 60), the computing device 60 may send a signal indicative of a validation. The edge device 70 may process this validation to push the controller parameters to the controller controlling (e.g., actuating the operating parameter of) the device and actuate the operating parameter. In this example, the controller parameters (e.g., controller gains, etc.) are pushed to the controller controlling the inlet bleed heat valve, which would open or close accordingly to achieve a settling time of less than five seconds for the compressor inlet bleed temperature.
Alternatively, if the controller parameters and/or plant characteristics are not approved by the plant operator, the plant operator may send via the computing device 60 a signal indicative of a rejection. The edge device 70 may receive this signal of the rejection along with alternative (e.g., different) plant characteristics,
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which would result in the edge device 70 determining the controller parameters (block 128) again. The flow diagram 120 would accordingly proceed as illustrated in FIG. 4.
Technical effects of the present disclosure include tuning controllers remotely to cause a change in operating parameter by adjusting gains of a controller that controls operation of a system and/or its component(s). The system and/or component of the system may be a compressor, gas turbine, rotor blade, or any other suitable component of industrial machinery. In some embodiments, an edge device may receive an indication to perturb the system, thereby altering an operating parameter. After the system is perturbed, the edge device 70 may collect the system response data (e.g., real-time data) and may send the data of the system response to a computing device and/or a cloud service. The edge device 70 may calculate (e.g., tune) the gains of the controller, and/or any other controller parameters. In certain embodiments, the calculations performed by the edge device 70 may be based at least in part on target plant characteristics from the computing device. Once approved, the controller parameters may be pushed onto (e.g., implemented by) the controller.
This written description uses examples to disclose the embodiments, including the best mode, and to enable any person skilled in the art to practice the embodiments, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the disclosure is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal language of the claims.
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WE CLAIM:
1. A computing device comprises:
a display;
one or more processors; and
memory storing instructions, wherein the instructions are configured to cause the one or more processors to:
receive an indication of a process of industrial machinery to be tuned to cause an operating parameter of the industrial machinery to change thereby causing perturbation of operation of the industrial machinery;
receive response data indicative of a response of the industrial machinery to the perturbation of operation of the industrial machinery;
determine one or more controller parameters based at least in part on the response data;
display the one or more controller parameters via the display; and
cause the one or more controller parameters to be pushed to a controller of the industrial machinery.
2. The computing device as claimed in claim 1, the computing device comprises a cellular phone, a laptop, or a tablet.
3. The computing device as claimed in claim 1, wherein the industrial machinery comprises a gas turbine system.
4. The computing device as claimed in claim 3, wherein the operating parameter comprises an inlet bleed heat of the gas turbine system, inlet gas temperature of gas entering the gas turbine system, inlet pressure of gas exiting the gas turbine system, or any combination thereof.
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5. The computing device as claimed in claim 1, wherein determining the one or more controller parameters comprises calculating the one or more controller parameters using the one or more processors.
6. The computing device as claimed in claim 1 comprising an interface that is configured to connect with an edge device for the industrial machinery, wherein determining the one or more controller parameters comprises using the edge device to calculate the one or more controller parameters via the interface.
7. The computing device as claimed in claim 1, wherein the instructions are configured to cause the one or more processors to:
simulate a closed loop operation of the industrial machinery as a simulation using the one or more controller parameters; and
display results of the simulation.
8. The computing device as claimed in claim 8, wherein the instructions are configured to cause the one or more processors to request confirmation of the results as valid before pushing the one or more controller parameters to the controller of the industrial machinery.
9. The computing device as claimed in claim 1, wherein causing the one or more controller parameters to be pushed to a controller of the industrial machinery, comprises performing a closed loop step response on the plant.
10. A tangible, non-transitory, and computer-readable medium having instructions stored thereon that, when executed by a processor of an edge device of industrial machinery that couples a controller of a plant to outside devices, are configured to cause the processor to:
collect system response data to a perturbation of operation of a plant;
send the system response data indicative of system response of the plant to a computing device and a cloud service;
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calculate controller parameters based on one or more target system response parameters;
receive a validation from the computing device, wherein the validation is an indication of approval of the controller parameters; and
push the controller parameters to a controller on the plant.
11. The tangible, non-transitory, and computer-readable medium as claimed in claim 10, wherein the processor receives an indication of a tuning from the computing device and sends the indication of the tuning to the plant to cause the perturbation of operation of the plant.
12. The tangible, non-transitory, and computer-readable medium as claimed in claim 10, wherein the instructions are configured to cause the processor determine from the system response data:
plant characteristics; or
controller gains.
13. The tangible, non-transitory, and computer-readable medium as
claimed in claim 12, wherein the plant characteristics comprise:
a transfer function of the plant;
rise time for a response for the plant;
settling time for the response for the plant;
closed loop bandwidth; open loop stability margins; or any combination thereof.
14. The tangible, non-transitory, and computer-readable medium as
claimed in claim 10, wherein the instructions are configured to cause the edge
device processor to send an indication indicative of the control parameters to the
controller of the plant, wherein the indication of the control parameters causes the
control parameters to be pushed to the controller of the plant.
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15. The tangible, non-transitory, and computer-readable medium as
claimed in claim 10, wherein the instructions are configured to cause the
processor to:
communicate with the controller of the plant; and
communicate with a cloud services.
16. An industrial machinery system comprising:
industrial machinery comprising a controller;
an edge device coupled to the controller and a computing device, wherein the edge device comprises:
a processor; and
memory storing instructions configured to cause the processor to:
receive an indication of a perturbation to at least one operating parameter of the industrial machinery from the computing device;
collect response data indicative of the response of the industrial machinery to the perturbation from the controller;
determine one or more controller parameters based at least in part on the response of the industrial machinery relative to the target response; and
push the one or more controller parameters to the controller.
17. The industrial machinery system as claimed in claim 16, wherein
determining the one or more controller parameters comprises determining a
structure of the controller and gains associated with the controller.
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18. The industrial machinery system as claimed in claim 17, wherein determining the structure of the controller comprises characterizing the controller as a proportional-integral (PI) controller, a proportional-derivative (PD) controller, or a proportional-integral-derivate (PID) controller, determining a lead-lag compensator, or utilizing polynomial pole placement.
19. The industrial machinery system as claimed in claim 17, wherein pushing the one or more controller parameters to the controller comprises implementing the gains in the controller.
20. The industrial machinery system as claimed in claim 16, wherein the instructions are configured to cause the processor to simulate operation of the industrial machinery as a simulation using the one or more controller parameters, and wherein pushing the one or more controller parameters to the controller comprises receiving a verification that the simulation is acceptable from the computing device before pushing the one or more controller parameters to the controller of the industrial machinery.