Description:DESCRIPTION

Technical Field
This disclosure relates generally to proportional valves, and more particularly to a method and a system for optimizing proportional valve response for proportional valves implemented in ventilators.

Background
Control systems typically suffer from time delay (also referred to as response delay) problems. For example, in ventilators, proportional valves are used for timely delivery of Oxygen gas in closed loop oxygen control system to control SpO2 and timely delivery of other drugs. These proportional valves have a time delay due to their mechanical construction. A feedback loop configuration may be implemented in the proportional valve systems for overcoming the problem of time delay. However, feedback loop may not yield satisfactory results.
There is, therefore, a need for optimizing proportional valve response by using a predictive model.

SUMMARY
A method of optimizing proportional valve response is disclosed. In some embodiments, the method may include receiving an actuation signal inputted to a proportional valve actuator, for actuation of the proportional valve actuator for generating an outflow of a gas via the proportional valve actuator. The method may further include receiving a feedback signal from a flow sensor corresponding to a response of the proportional valve actuator to the actuation signal for generating the outflow of the gas via the proportional valve actuator. The flow sensor may be positioned at an outlet gate of the proportional valve actuator. The method may further include analysing the actuation signal and the feedback signal to determine a time-delay associated with the response of the proportional valve actuator. The method may further include determining a transfer function associated with the proportional valve actuator. determining, using a predictive model, a correction factor for the response of the proportional valve actuator, to optimize the proportional valve response, based on the time-delay and the transfer function.
Additionally, the method may include receiving a test actuation signal inputted to the proportional valve actuator, for actuation of the proportional valve actuator, and further receiving a set point corresponding to the test actuation signal for generating the outflow of the gas via the proportional valve actuator. Further, the method may include optimizing the proportional valve response, based on the correction factor, to minimize the time required for the outflow of the gas to reach the set point.
Further, a system for optimizing proportional valve response is disclosed. In some embodiments, the system may include a proportional valve actuator which may include an inlet gate for receiving a supply of a gas and an outlet gate for releasing an outflow of the gas. The system may further include a flow sensor positioned at the outlet gate of the proportional valve actuator. Further, the system may include a predictive controller which may include a processor and a memory communicatively coupled with the processor. The memory stores processor-executable instructions which, on execution by the processor, cause the processor to receive an actuation signal inputted to the proportional valve actuator, for actuation of the proportional valve actuator for generating an outflow of the gas via the proportional valve actuator and receive a feedback signal from the flow sensor corresponding to a response of the proportional valve actuator to the actuation signal for generating the outflow of the gas. The processor-executable instructions, on execution by the processor, further cause the processor to analyse the actuation signal and the feedback signal to determine a time-delay associated with the response of the proportional valve actuator. The memory stores processor-executable instructions, on execution by the processor, further cause the processor to determine a transfer function associated with the proportional valve actuator, and determine, using a predictive model, a correction factor for the response of the proportional valve actuator, to optimize the proportional valve response, based on the transfer function.
Furthermore, a system for optimizing proportional valve response is disclosed. The system may include an actual proportional valve actuator that may include an inlet gate for receiving a supply of a gas and an outlet gate for releasing an outflow of the gas. A time-delay may be associated with the actual proportional valve actuator. The system may further include an actual flow sensor positioned at the outlet gate of the actual proportional valve actuator, a predictive controller, and an optimizing device implementing a proportional valve actuator model. The optimizing device may be configured to receive an actuation signal inputted to the actual proportional valve actuator, for actuation of the actual proportional valve actuator for generating an outflow of the gas via the actual proportional valve actuator, receive a feedback signal from the actual flow sensor corresponding to an actual output from the actual proportional valve actuator, and obtain, from the proportional valve actuator model, a model output. The model output may be determined based on a transfer function associated with the proportional valve actuator model. The optimizing device may be further configured to analyse the actual output and the model output, using a predictive model to determine a correction factor for the response of the proportional valve actuator, based on the time-delay and the transfer function and implement the correction factor on the predictive controller to optimize the proportional valve response associated with the actual proportional valve actuator.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS
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.
FIG. 1 is a block diagram of a system for optimizing proportional valve response, in accordance with an embodiment of the present disclosure.
FIG. 2 is a schematic diagram of a model-based system (corresponding to the model-based system of FIG. 1) for optimizing proportional valve response, in accordance with an embodiment of the present disclosure.
FIG. 3 illustrates a schematic representation of a transfer function, in accordance with an embodiment of the present disclosure.
FIG. 4 is a graphical representation of a response of the predictive controller with the Smith predictor model and without the Smith predictor model, in accordance with an embodiment of the present disclosure.
FIG. 5 is a graphical representation of a response of the predictive controller with the Smith predictor model as implemented in a ventilator, in accordance with an embodiment of the present disclosure.
FIG. 6 is a flowchart of a method of optimizing proportional valve response, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION
Exemplary embodiments are described with reference to the accompanying drawings. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the spirit and scope of the disclosed embodiments. It is intended that the following detailed description be considered as exemplary only, with the true scope and spirit being indicated by the following claims. Additional illustrative embodiments are listed below.
One or more techniques for optimizing proportional valve response are disclosed. The techniques use Smith predictor to improve response of the Proportional Integral Derivative (PID) on the proportional valve flow outlet. The current techniques use the time delay model of the proportional valve flow response and the Smith predictor to improve the response of proportional valve.
According to an embodiment of the present disclosure, a system includes a proportional valve actuator model along with a predictive controller (also referred to as proportional integral derivative (PID) controller) and one or more flow sensors, for improving response of the proportional valve actuator. As will be understood by those skilled in the art, the proportional valve actuators (or simply proportional valves) have some amount of response delay in the current input and flow output, due to their mechanical construction. This response delay causes control difficulty when there are rapid flow changes.
To this end, the current techniques, based on theoretical modeling, implement a Smith predictor algorithm to improve the response of proportional valve, to thereby enable rapid flow changes. The flow sensor measures the flow reading of the flow from the proportional valve, and provide feedback to the predictive controller. The proportional valve and the flow sensor are modelled and a transfer function associated with the model is used to predict the flow output from the proportional valve. The Smith predictor-based predictive controller compares the model output (having no response delay) and an actual output, and provides the best response possible. In other words, the response from the predictive controller is optimized to overcome the response delay. The proportional valve model has current as an input and flow as an output. The response delay of the proportional valve output is experimentally calculated and optimized using the Smith predictor. The Smith predictor-based optimization achieves better control of proportional valve and fast flow delivery in the ventilator as compared to normal PID controllers. The Smith predictor algorithm uses a mathematical transfer function to predict the flow output of the device based on current input. Further, this model is a second order transfer function system model which does not include the time delay of the proportional valve actuator. The time delay is independently calculated experimentally which is then added to the system model to improve the response of the predictive controller. In an alternate embodiment, the time delay is calculated in real-time and then added to the system model to improve the response of the predictive controller.
The system may include a gas manifold which provides high-pressure gas flow inlet to the proportional valve. The proportional valve (actuator) may have a linear motor which opens the valve orifice based on the current provided. Electric current may be provided to the actuator by a PID controller which may implement the Smith predictor model. It should be further noted that the Smith predictor model is disclosed merely as an example, and any other predictive model may be used as well. for example, a Model Predictive Control (MPC) may be used to improve the response delay in the above system.
A flow output given by proportional valve is sensed by flow sensor. The flow sensor gives feedback to the controller to predict the next step output flow and thus improving the PID response. The Smith predictor model may use a mathematical transfer function to predict the flow output of the device based on current input. Further, this model may be a second order transfer function system model which does not include the time delay of the actuator.
The time delay may be independently calculated experimentally which may be then added to the algorithm to improve the response of the PID controller. In an alternate embodiment, the time delay may be calculated in real-time and algorithm to improve the response of the PID controller.
In one embodiment, a block diagram of a system 100 for optimizing proportional valve response is illustrated in FIG. 1, in accordance with an embodiment of the present disclosure. The system 100 may include a proportional valve actuator 102, a flow sensor 108, and a predictive controller 106. The proportional valve actuator 102 may include an inlet gate 102A for receiving a supply of a gas and an outlet gate 102B for releasing an outflow of the gas. The proportional valve actuator 102 may be connected to a gas manifold 104, via the inlet gate 102A, that may provide a supply of a gas, for example, Oxygen gas, via the outlet gate 102B. As such, the supply from the gas manifold 104 may be routed through the proportional valve actuator 102, such that the proportional valve actuator 102 controls the flow of the gas from the gas manifold 104.
The proportional valve actuator 102 is communicatively coupled to the predictive controller 106. The predictive controller 106 may provide signals (instructions) to the proportional valve actuator 102, to control the flow of the gas from the gas manifold 104. In order to control the flow of the gas, an actuation signal may be inputted to the proportional valve actuator 102, for actuation of the proportional valve actuator 102, to thereby generate an outflow of a gas via the proportional valve actuator 102. The actuation signal may be generated based on an input from a user, for example, a doctor or a nursing staff setting the Oxygen flow rate. The same actuation signal may be received by the predictive controller 106.
As will be appreciated, the proportional valve actuator 102 may have a mechanical construction and may implement a number of mechanical components for controlling the flow of the gas. Due to their mechanical construction, the proportional valves may have some amount of response delay in the current input and flow output. This response delay causes control difficulty when there are rapid flow changes. Further, the proportional valve actuator 102, for example, may be operable by a linear electric motor.
The flow sensor 108, as shown in FIG. 1, is positioned at an outlet gate of the proportional valve actuator 102. The flow sensor 108 generates a feedback signal corresponding to a response of the proportional valve actuator 102 to an actuation signal for generating the outflow of the gas via the proportional valve actuator 102. The feedback signal is received by the predictive controller 106 from the flow sensor 108 corresponding to the response of the proportional valve actuator 102 to the actuation signal. The predictive controller 106, therefore, received both the actuation signal and the feedback signal.
The predictive controller 106 may analyse the actuation signal and the feedback signal to determine a time-delay associated with the response of the proportional valve actuator. Based on the analysis, the predictive controller 106 may further determine a transfer function associated with the proportional valve actuator 102.
In some embodiments, the predictive controller 106 may implement a predictive model. Further, in some embodiments, the predictive model may be a Smith predictor model. It should be noted that, in some embodiments, the Smith predictor model may use a second order transfer function that is independent of the time delay of the actuator. The predictive controller 106, using the predictive model, may determine a correction factor for the response of the proportional valve actuator 102, to thereby optimize the proportional valve response, based on the time-delay and the transfer function. In particular, the predictive controller 106 may be provided a test run so as to configure the predictive controller 106 for future real time optimization. To this end, the predictive controller 106 may receive a test actuation signal inputted to the proportional valve actuator 102, for actuation of the proportional valve actuator 102 for generating an outflow of the gas via the proportional valve actuator 102. Further, the predictive controller 106 may receive a set point corresponding to the test actuation signal for generating the outflow of the gas via the proportional valve actuator 102. The predictive controller 106 may then optimize the proportional valve response, based on the correction factor, to minimize the time required for the outflow of the gas to reach the set point.
The predictive controller 106 may be a computing device having data processing capability. In particular, the predictive controller 106 may have capability for optimizing the proportional valve response, and in particular for overcoming the time delay associated with the proportional valve actuator 102. Examples of the predictive controller 106 may include, but are not limited to a desktop, a laptop, a notebook, a netbook, a tablet, a smartphone, a mobile phone, an application server, a web server, or the like. In some example embodiments, the predictive controller 106 may be a cloud-based computing system. Further, in some example embodiments, the predictive controller 106 may be a microcontroller implemented in the proportional valve actuator 102 itself.
Further, in order to perform the above-discussed functionalities, the predictive controller 106 may include a processor 110 and a memory 112. The memory 112 may store instructions that, when executed by the processor 110, cause the processor 110 to perform testing of the ventilators, as discussed in greater detail in FIG. 2 to FIG. 4. The memory 112 may be a non-volatile memory or a volatile memory. Examples of the non-volatile memory may include, but are not limited to, a flash memory, a Read Only Memory (ROM), a Programmable ROM (PROM), Erasable PROM (EPROM), and Electrically EPROM (EEPROM) memory. Examples of volatile memory may include, but are not limited to, Dynamic Random Access Memory (DRAM), and Static Random-Access memory (SRAM). The memory 112 may also store various data (e.g. transfer function data, time-delay data, etc.) that may be captured, processed, and/or required by the system 100.
Referring now to FIG. 2, a schematic diagram of a system 200 (corresponding to the model-based system 100) for optimizing proportional valve response, in accordance with some embodiments. As shown in FIG. 2, the model-based system 200 may include an actual proportional valve actuator 204 (also referred to as device 204 - as such, the terms device and actual proportional valve actuator may have been used interchangeably in this disclosure). The device 204 may include an inlet gate (not shown in FIG. 2) for receiving a supply of a gas and an outlet gate for releasing an outflow of the gas (not shown in FIG. 2). For example, the actual proportional valve actuator 204 may be a two-way normally closed valve, having power specification of 2 Watts. It should be noted that a time-delay is associated with the actual proportional valve actuator 204. For example, the time-delay may be 200 milli seconds (ms).
The system 200 may further include an actual flow sensor (not shown in FIG. 2) positioned at the outlet gate of the actual proportional valve actuator 204. The actual flow sensor may have a span accuracy of less than 3% of the reading, and a response time of 3 ms. The system 200 may further include a predictive controller 202 which may be communicatively coupled with the actual proportional valve actuator 204. The predictive controller 202 may be configured to control the functioning of the actual proportional valve actuator 204. For example, the predictive controller 202 may have a set point defined at flow rate of 80 slpm. Further, the required PWM may be 100% duty cycle. The predictive controller 202 may be configured to operate at a frequency of 168 MHz
The system 200 may further include an optimizing device. The optimizing device may be a computing device having data processing capability. In particular, the optimizing device may have capability for optimizing the proportional valve response, and in particular for overcoming the time delay existing with the actual proportional valve actuator 204. Examples of the optimizing device may include, but are not limited to a desktop, a laptop, a notebook, a netbook, a tablet, a smartphone, a mobile phone, an application server, a web server, or the like. In some example embodiments, the optimizing device may be a cloud-based computing system.
The optimizing device may implement a proportional valve actuator model 206 (also referred to as device model 206 – the terms device model 206 and proportional valve actuator model 206 may have been used interchangeable in this disclosure). The optimizing device may receive an actuation signal inputted to the actual proportional valve actuator 204 for actuation of the actual proportional valve actuator 204. Further, the optimizing device may receive a feedback signal from the actual flow sensor corresponding to an actual output from the actual proportional valve actuator 204. The optimizing device may further obtain a model output, from the proportional valve actuator model. The model output may be predicted based on a transfer function associated with the proportional valve actuator model.
The optimizing device may analyse the actual output and the model output, using a predictive model to determine a correction factor for the response of the proportional valve actuator, based on the time-delay and the transfer function. Further, the optimizing device may implement the correction factor on the predictive controller 202 to optimize the proportional valve response associated with the actual proportional valve actuator 204.
During operation, a flow rate set point 210 (or simply the set point 210) may be obtained. The flow rate set point 210 corresponds to the actuation signal for generating the outflow of the gas via the actual proportional valve actuator 204. The flow rate set point 210 may be fed into the predictive controller 202. As mentioned above, the actual proportional valve actuator 204 may have some response delay 208 (i.e. time delay).
In some embodiments, the predictive controller 202 may receive the actuation signal inputted to the proportional valve actuator model 206, for actuation of the proportional valve actuator model 206 for generating an outflow of the gas via the proportional valve actuator. Further, the the predictive controller 202 may receive the set point 210 corresponding to the test actuation signal for generating the outflow of the gas via the proportional valve actuator. Furthermore, a flow sensor output 212 (i.e. a feedback signal 212) is received from a flow sensor (not shown in FIG. 2) corresponding to a response of the proportional valve actuator model 206 to the actuation signal for generating the outflow of the gas via the proportional valve actuator model 206. As mentioned above, the flow sensor may be positioned at an outlet gate of the proportional valve actuator model 206.
In some example embodiments, the predictive controller 202 may analyse the actuation signal and the feedback signal to: determine a time-delay associated with the response of the proportional valve actuator. In alternate embodiments, the response delay of the device may be independently calculated experimentally. This response delay may then be added to the Smith predictor model implemented in the PID controller.
The predictive controller 202 may further determine a transfer function associated with the proportional valve actuator model 206. The transfer function is further depicted via a schematic diagram illustrated in FIG. 3. As shown in FIG. 3, a transfer function 302 may have a pulse-width modulation (PWM) input 304 and a flow output 306. In other words, the input to the transfer function 302 may be an electronic signal from the predictive controller and the output from the transfer function 302 may be a value associated with a flow from actual proportional valve actuator model. As such, the Smith predictor model implemented in the predictive controller uses the mathematical transfer function to predict the flow output of the device based on current input. The transfer function, for example, may be a second order transfer function which does not include the time delay (i.e. the response delay) of the proportional valve actuator. For example, for the second order transfer function, its Laplace form is as below:
T(s)=(0.5659s+0.0141)/(s^2+1.092s+0.0246)
F(s)=T(s)I(s)
where, F(s) is Laplace transform of output flow from the device and I(s) is Laplace transform of input PWM signal.

Returning to FIG. 2, the predictive controller 202 may then determine a correction factor for the response of the proportional valve actuator 206, using the Smith predictor model. The correction factor is then implemented in the actual proportional valve actuator 204 to optimize the response of the actual proportional valve actuator 204, based on the time-delay and the transfer function. In particular, the proportional valve response is optimized, based on the correction factor, to minimize the time required for the outflow of the gas to reach the set point. After the Smith predictor model is added, the response of predictive controller 202 becomes robust and faster. This is depicted via a graphical representation as illustrated in FIG. 4.
Referring now to FIG. 4, a graphical representation 400 of a response of the predictive controller with the Smith predictor model and without the Smith predictor model are illustrated, in accordance with some embodiments. As shown in FIG. 4, the graphical representation 400 is plotted against flow rate (standard liters per minute or “slpm”) along the y-axis and time (seconds or “s”) along the x-axis. Curve 402 corresponds to the response of the predictive controller implemented with the Smith predictor model. Curve 404 corresponds to the response of the predictive controller without the Smith predictor model. As can be understood, the response of the predictive controller with the Smith predictor model (curve 404) is faster and smoother.
Returning once again to FIG. 2, the device 204 may be implemented in variety of application areas, including ventilators for providing respiratory support to patients. The device with implemented the Smith predictor model may improve flow delivery response in the ventilator which further is useful in maintaining (Peak Inspiratory Pressure (PIP) and flow rate in pressure control and volume control modes respectively. This is depicted via a graphical representation as illustrated in FIG. 5.
Referring now to FIG. 5, a graphical representation 500 of a response of the predictive controller with the Smith predictor model as implemented in a ventilator is illustrated, in accordance with some embodiments. As shown in FIG. 5, the graphical representation 500 is plotted against pressure along the y-axis and time along the x-axis. Curve 502 corresponds to the response of the predictive controller implemented with the Smith predictor model. As can be understood from the curve 502, the predictive controller with the Smith predictor model provides an improved rise time during the PIP. In other words, the rise time during the PIP is reduced, thereby making the response of the ventilator faster and more robust. Further, this is also useful in controlling PEEP (Positive End Expiratory Pressure) with bias flow as the control becomes faster. It should be noted that the above method and system may not be limited to mechanical ventilators, and may be used in other flow delivery system having actuator response delay.
Referring now to FIG. 6, a flowchart of a method 600 of optimizing proportional valve response illustrated, in accordance with some embodiments. In some embodiments, the method 600 may be performed by the predictive controller 106 (or the predictive controller 202).
At step 602, an actuation signal inputted to the proportional valve actuator 102 may be received. The actuation signal may be inputted to the proportional valve actuator 102 for actuation of the proportional valve actuator 102 for generating an outflow of a gas via the proportional valve actuator 102. For example, the proportional valve actuator 102 may be operable by a linear electric motor.
At step 604, a feedback signal may be received from the flow sensor 108 corresponding to a response of the proportional valve actuator 102 to the actuation signal for generating the outflow of the gas via the proportional valve actuator 102. The flow sensor 108 may be positioned at an outlet gate of the proportional valve actuator 102.
At step 606, the predictive controller 106 may analyse the actuation signal and the feedback signal to: determine a time-delay associated with the response of the proportional valve actuator 102. In some example embodiments, simultaneously with step 606, at step 608, the predictive controller 106 may determine a transfer function associated with the proportional valve actuator 102. In some example embodiments, the transfer function associated with the proportional valve actuator 102 may be a second order transfer function.
At step 610, a correction factor may be determined for the response of the proportional valve actuator, using a predictive model, based on the time-delay and the transfer function. For example, the predictive model may be a Smith predictor model. Further, in some example embodiments, the Smith predictor model may use a second order transfer function that is independent of the time delay of the actuator. The correction factor may then be implemented in the proportional valve actuator 102, to optimize the proportional valve response. The correction factor may be implemented in the proportional valve actuator 102 and in particularly in the predictive controller 106 to thereby optimize the proportional valve response.
As will be also appreciated, the above-described techniques may take the form of computer or controller implemented processes and apparatuses for practicing those processes. The disclosure can also be embodied in the form of computer program code containing instructions embodied in tangible media, such as floppy diskettes, solid state drives, CD-ROMs, hard drives, or any other computer-readable storage medium, wherein, when the computer program code is loaded into and executed by a computer or controller, the computer becomes an apparatus for practicing the invention. The disclosure may also be embodied in the form of computer program code or signal, for example, whether stored in a storage medium, loaded into and/or executed by a computer or controller, or transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing the invention. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits.
The disclosed methods and systems may be implemented on a conventional or a general-purpose computer system, such as a personal computer (PC) or server computer. It will be appreciated that, for clarity purposes, the above description has described embodiments of the invention with reference to different functional units and processors. However, it will be apparent that any suitable distribution of functionality between different functional units, processors or domains may be used without detracting from the invention. For example, functionality illustrated to be performed by separate processors or controllers may be performed by the same processor or controller. Hence, references to specific functional units are only to be seen as references to suitable means for providing the described functionality, rather than indicative of a strict logical or physical structure or organization.
The above techniques provide for implementing a Smith predictor model to improve response of proportional integral derivative (PID) controller on the proportional valve flow outlet. Using the time delay model of the proportional valve flow response along with the Smith predictor model, the response of the proportional valve is improved.
It is intended that the disclosure and examples be considered as exemplary only, with a true scope and spirit of disclosed embodiments being indicated by the following claims.
, Claims:I/We claim:
1. A method of optimizing proportional valve response, the method comprising:
receiving, by a predictive controller (106), an actuation signal inputted to a proportional valve actuator (102), for actuation of the proportional valve actuator (102) for generating an outflow of a gas via the proportional valve actuator (102);
receiving, by the predictive controller (106), a feedback signal from a flow sensor (108) corresponding to a response of the proportional valve actuator (102) to the actuation signal for generating the outflow of the gas via the proportional valve actuator (102), wherein the flow sensor (108) is positioned at an outlet gate of the proportional valve actuator (102);
analysing, by the predictive controller (106), the actuation signal and the feedback signal to determine a time-delay associated with the response of the proportional valve actuator (102); and
determining, by the predictive controller (106), a transfer function associated with the proportional valve actuator (102); and
determining, by the predictive controller (106), using a predictive model, a correction factor for the response of the proportional valve actuator (102), based on the time-delay and the transfer function, to optimize the proportional valve response.

2. The method as claimed in claim 1, wherein the predictive model is a Smith predictor model.

3. The method as claimed in claim 1, wherein the transfer function associated with the proportional valve actuator is a second order transfer function.

4. The method as claimed in claim 2, wherein the Smith predictor model uses a second order transfer function that is independent of the time delay of the actuator.

5. The method as claimed in claim 1 further comprising:
receiving a test actuation signal inputted to the proportional valve actuator (102), for actuation of the proportional valve actuator (102) for generating an outflow of the gas via the proportional valve actuator (102);
receiving a set point (210) corresponding to the test actuation signal for generating the outflow of the gas via the proportional valve actuator (102); and
optimizing the proportional valve response, based on the correction factor, to minimize the time required for the outflow of the gas to reach the set point (210).

6. The method as claimed in claim 1, wherein the proportional valve actuator is (102) operable by a linear electric motor.

7. A system (100) for optimizing proportional valve response, the system (100) comprising:
a proportional valve actuator (102) comprising:
an inlet gate (102A) for receiving a supply of a gas; and
an outlet gate (102B) for releasing an outflow of the gas;
a flow sensor (108) positioned at the outlet gate (102B) of the proportional valve actuator (102); and
a predictive controller (106) comprising:
a processor (110); and
a memory (112) communicatively coupled with the processor (110) and storing processor-executable instructions which, on execution by the processor (110), cause the processor (110) to:
receive an actuation signal inputted to the proportional valve actuator (102), for actuation of the proportional valve actuator (102) for generating an outflow of the gas via the proportional valve actuator (102);
receive a feedback signal from the flow sensor (108) corresponding to a response of the proportional valve actuator (102) to the actuation signal for generating the outflow of the gas;
analyse the actuation signal and the feedback signal to:
determine a time-delay associated with the response of the proportional valve actuator (102); and
determine a transfer function associated with the proportional valve actuator (102); and
determine, using a predictive model, a correction factor for the response of the proportional valve actuator (102), to optimize the proportional valve response, based on the transfer function.

8. The system (100) as claimed in claim 7, wherein the processor-executable instructions further cause the processor (110) to:
receive a test actuation signal inputted to the proportional valve actuator (102), for actuation of the proportional valve actuator (102) for generating an outflow of the gas via the proportional valve actuator (102);
receive a set point (210) corresponding to the test actuation signal for generating the outflow of the gas via the proportional valve actuator (102), based on the correction factor; and
optimize the proportional valve response, based on the correction factor, to minimize the time required for the outflow of the gas to reach the set point (210).

9. The system (100) as claimed in claim 7, wherein the predictive model is a Smith predictor model.

10. A system (200) for optimizing proportional valve response, the system (200) comprising:
an actual proportional valve actuator (204) comprising:
an inlet gate for receiving a supply of a gas; and
an outlet gate for releasing an outflow of the gas;
wherein a time-delay is associated with the actual proportional valve actuator (204);
an actual flow sensor positioned at the outlet gate of the actual proportional valve actuator (204); and
a predictive controller (202);
an optimizing device implementing a proportional valve actuator model (206)),
the optimizing device configured to:
receive an actuation signal inputted to the actual proportional valve actuator (204), for actuation of the actual proportional valve actuator (204) for generating an outflow of the gas via the actual proportional valve actuator (204);
receive a feedback signal from the actual flow sensor corresponding to an actual output from the actual proportional valve actuator (204);
obtain, from the proportional valve actuator model, a model output, wherein the model output is determined based on a transfer function associated with the proportional valve actuator model;
analyse the actual output and the model output, using a predictive model to determine a correction factor for the response of the proportional valve actuator, based on the time-delay and the transfer function; and
implement the correction factor on the predictive controller (202) to optimize the proportional valve response associated with the actual proportional valve actuator (204).