The traditional integer order PID controller manipulates the air-conditioning fan coil unit(FCU)that offers cooliug and heatins loads to each air-conditioning room in summer and winter,respectivelv.In order to maintai...The traditional integer order PID controller manipulates the air-conditioning fan coil unit(FCU)that offers cooliug and heatins loads to each air-conditioning room in summer and winter,respectivelv.In order to maintain a steady indoor temperature in summer and winter,the control quality cannot meet the related requirements of air-conditioning automation,such as large overshoot,large steady state error.long regulating time,etc.In view of these factors,this paper develops a fractional order PID controller to deal with such problem associated with FCU.Then,by varving mutation factor and crossover rate of basic differential evolution algorithmadaptivelv,a modified differential evolution algorithm(MDEA)is designed to tune the satisfactory values of five parameters of indoor temperature fractional order PID controller.This fractional order PID coutrol system is configured and the corresponding mumerical simulation is conducted by means of MATLAB software.The results indicate that the proposed fractional order PID control svstem and MDEA are reliable and the related control performance indexes meet with the related requirements of comfortable air-conditioning design and control criteria.展开更多
Core power is a key parameter of nuclear reactor.Traditionally,the proportional-integralderivative(PID)controllers are used to control the core power.Fractional-order PID(FOPID)controller represents the cutting edge i...Core power is a key parameter of nuclear reactor.Traditionally,the proportional-integralderivative(PID)controllers are used to control the core power.Fractional-order PID(FOPID)controller represents the cutting edge in core power control research.In comparing with the integer-order models,fractional-order models describe the variation of core power more accurately,thus provide a comprehensive and realistic depiction for the power and state changes of reactor core.However,current fractional-order controllers cannot adjust their parameters dynamically to response the environmental changes or demands.In this paper,we aim at the stable control and dynamic responsiveness of core power.Based on the strong selflearning ability of artificial neural network(ANN),we propose a composite controller combining the ANN and FOPID controller.The FOPID controller is firstly designed and a back propagation neural network(BPNN)is then utilized to optimize the parameters of FOPID.It is shown by simulation that the composite controller enables the real-time parameter tuning via ANN and retains the advantage of FOPID controller.展开更多
Active disturbance rejection controller（ADRC）uses tracking-differentiator（TD）to solve the contradiction between the overshoot and the rapid nature.Fractional order proportion integral derivative（PID）controller i...Active disturbance rejection controller（ADRC）uses tracking-differentiator（TD）to solve the contradiction between the overshoot and the rapid nature.Fractional order proportion integral derivative（PID）controller improves the control quality and expands the stable region of the system parameters.ADRC fractional order（ADRFO）PID controller is designed by combining ADRC with the fractional order PID and applied to reentry attitude control of hypersonic vehicle.Simulation results show that ADRFO PID controller has better control effect and greater stable region for the strong nonlinear model of hypersonic flight vehicle under the influence of external disturbance,and has stronger robustness against the perturbation in system parameters.展开更多
In this paper,simulated and experimental results on the conical tank level control are presented.PI/PID controllers of integer order(IO)as well as of fractional order(FO)are studied and compared.The tuning parameters ...In this paper,simulated and experimental results on the conical tank level control are presented.PI/PID controllers of integer order(IO)as well as of fractional order(FO)are studied and compared.The tuning parameters are obtained first by using root locus(RL)and Ziegler and Nichols methods,for comparison purposes.Next,particle swarm optimization(PSO)is employed to determine the optimal controllers'parameters using as fitness function the integral of the absolute value of tracking error(IAE).From the experimental results it is concluded that PI/FOPI are the controllers presenting the lowest IAE indexes,whereas PID/FOPID controllers present the lowest energy consumption by the control signal.展开更多
The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(M...The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS),which is inherently nonlinear and unstable system.The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller.An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored.The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique.Effectiveness of the proposed control scheme is verified by simulation and experimental results.The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers.It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.展开更多
A new discretization scheme is proposed for the design of a fractional order PID controller. In the design of a fractional order controller the interest is mainly focused on the s-domain, but there exists a difficult ...A new discretization scheme is proposed for the design of a fractional order PID controller. In the design of a fractional order controller the interest is mainly focused on the s-domain, but there exists a difficult problem in the s-domain that needs to be solved, i.e. how to calculate fractional derivatives and integrals efficiently and quickly. Our scheme adopts the time domain that is well suited for Z-transform analysis and digital implementation. The main idea of the scheme is based on the definition of Grünwald-Letnicov fractional calculus. In this case some limited terms of the definition are taken so that it is much easier and faster to calculate fractional derivatives and integrals in the time domain or z-domain without loss much of the precision. Its effectiveness is illustrated by discretization of half-order fractional differential and integral operators compared with that of the analytical scheme. An example of designing fractional order digital controllers is included for illustration, in which different fractional order PID controllers are designed for the control of a nonlinear dynamic system containing one of the four different kinds of nonlinear blocks: saturation, deadzone, hysteresis, and relay.展开更多
3-RRR planar parallel robots are utilized for solving precise material-handling problems in industrial automation applications.Thus,robust and stable control is required to deliver high accuracy in comparison to the s...3-RRR planar parallel robots are utilized for solving precise material-handling problems in industrial automation applications.Thus,robust and stable control is required to deliver high accuracy in comparison to the state of the art.The operation of the mechanism is achieved based on three revolute(3-RRR)joints which are geometrically designed using an open-loop spatial robotic platform.The inverse kinematic model of the system is derived and analyzed by using the geometric structure with three revolute joints.The main variables in our design are the platform base positions,the geometry of the joint angles,and links of the 3-RRR planar parallel robot.These variables are calcula ted based on Cayley-Menger determinants and bilateration to det ermine the final position of the platform when moving and placing objects.Additionally,a proposed fractional order proportional integral derivative(FOPID)is optimized using the bat optimization algorithm to control the path tracking of the center of the 3-RRR planar parallel robot.The design is compared with the state of the art and simulated using the Matlab environment to validate the effectiveness of the proposed controller.Furthermore,real-time implementation has been tested to prove that the design performance is practical.展开更多
Interacting The highest storage capacity of a circular tank makes it pop-ular in process industries.Because of the varying surface area of the cross-sec-tions of the tank,this two-tank level system has nonlinear chara...Interacting The highest storage capacity of a circular tank makes it pop-ular in process industries.Because of the varying surface area of the cross-sec-tions of the tank,this two-tank level system has nonlinear characteristics.Controlling theflow rate of liquid is one of the most difficult challenges in the production process.This proposed effort is critical in preventing time delays and errors by managing thefluid level.Several scholars have explored and explored ways to reduce the problem of nonlinearity,but their techniques have not yielded better results.Different types of controllers with various techniques are implemented by the proposed system.Sliding Mode Controller(SMC)with Fractional Order PID Controller based on Intelligent Adaptive Neuro-Fuzzy Infer-ence System(ANFIS)is a novel technique for liquid level regulation in an inter-connected spherical tank system to avoid interferences and achieve better performance in comparison of rise time,settling time,and overshoot decrease.Evaluating the simulated results acquired by the controller yields the efficiency of the proposed system.The simulated results were produced using MATLAB 2018 and the FOMCON toolbox.Finally,the performance of the conventional controller(FOPID,PID-SMC)and proposed ANFIS based SMC-FOPID control-lers are compared and analyzed the performance indices.展开更多
Wind energy sources have different structures and functions from conventional power plants in the power system.These resources can affect the exchange of active and reactive power of the network.Therefore,power system...Wind energy sources have different structures and functions from conventional power plants in the power system.These resources can affect the exchange of active and reactive power of the network.Therefore,power system stability will be affected by the performance of wind power plants,especially in the event of a fault.In this paper,the improvement of the dynamic stability in power system equipped by wind farm is examined through the supplementary controller design in the high voltage direct current(HVDC)based on voltage source converter(VSC)transmission system.In this regard,impacts of the VSC HVDC system and wind farm on the improvement of system stability are considered.Also,an algorithm based on controllability(observability)concept is proposed to select most appropriate and effective coupling between inputs-outputs(IO)signals of system in different work conditions.The selected coupling is used to apply damping controller signal.Finally,a fractional order PID controller(FO-PID)based on exchange market algorithm(EMA)is designed as damping controller.The analysis of the results shows that the wind farm does not directly contribute to the improvement of the dynamic stability of power system.However,it can increase the controllability of the oscillatory mode and improve the performance of the supplementary controller.展开更多
In this study,a bald eagle optimizer(BEO)is used to get optimal parameters of the fractional-order proportional-integral-derivative(FOPID)controller for load frequency control(LFC).SinceBEOtakes only a very short time...In this study,a bald eagle optimizer(BEO)is used to get optimal parameters of the fractional-order proportional-integral-derivative(FOPID)controller for load frequency control(LFC).SinceBEOtakes only a very short time in finding the optimal solution,it is selected for designing the FOPID controller that improves the system stability and maintains the frequency within a satisfactory range at different loads.Simulations and demonstrations are carried out using MATLAB-R2020b.The performance of the BEOFOPID controller is evaluated using a two-zone interlinked power system at different loads and under uncertainty of wind and solar energies.The robustness of the BEO-FOPID controller is examined by testing its performance under varying system time constants.The results obtained by the BEOFOPID controller are compared with those obtained by BEO-PID and PID controllers based on recent metaheuristics optimization algorithms,namely the sine-cosine approach,Jaya approach,grey wolf optimizer,genetic algorithm,bacteria foraging optimizer,and equilibrium optimization algorithm.The results confirm that the BEO-FOPID controller obtains the finest result,with the lowest frequency deviation.The results also confirm that the BEOFOPID controller is stable and robust at different loads,under varying system time constants,and under uncertainty of wind and solar energies.展开更多
In this research,a modified fractional order proportional integral derivate(FOPID)control method is proposed for the photovoltaic(PV)and thermoelectric generator(TEG)combined hybrid renewable energy system.The faster ...In this research,a modified fractional order proportional integral derivate(FOPID)control method is proposed for the photovoltaic(PV)and thermoelectric generator(TEG)combined hybrid renewable energy system.The faster tracking and steady-state output are aimed at the suggested maximum power point tracking(MPPT)control technique.The derivative order number(μ)value in the improved FOPID(also known as PIλDμ)control structure will be dynamically updated utilizing the value of change in PV array voltage output.During the transient,the value ofμis changeable;it’s one at the start and after reaching the maximum power point(MPP),allowing for strong tracking characteristics.TEG will use the freely available waste thermal energy created surrounding the PVarray for additional power generation,increasing the system’s energy conversion efficiency.A high-gain DC-DC converter circuit is included in the system to maintain a high amplitude DC input voltage to the inverter circuit.The proposed approach’s performance was investigated using an extensive MATLAB software simulation and validated by comparing findings with the perturbation and observation(P&O)type MPPT control method.The study results demonstrate that the FOPID controller-based MPPT control outperforms the P&O method in harvesting the maximum power achievable from the PV-TEG hybrid source.There is also a better control action and a faster response.展开更多
The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order ...The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative(FOPID)controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration.To improve load frequency control,the proposed controllers are applied to a two-area interconnectedmicrogrid system incorporating diverse energy sources,such as wind turbines,photovoltaic cells,diesel generators,and various storage technologies.A novelmeta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers.The efficacy of the advanced FOPID controllers is demonstrated through comparative analyses against traditional proportional integral derivative(PID)and FOPID controllers,showcasing superior performance inmanaging systemfluctuations.The optimization algorithm is also evaluated against other artificial intelligent methods for parameter optimization,affirming the proposed solution’s efficiency.The robustness of the intelligent controllers against system uncertainties is further validated under extensive power disturbances,proving their capability to maintain grid stability.The dual-controller configuration ensures redundancy,allowing them to operate as mutual backups,enhancing system reliability.This research underlines the importance of sophisticated control strategies for future-proofing microgrid operations against the backdrop of evolving energy landscapes.展开更多
The 3Φinduction motor is a broadly used electric machine in industrial applications,which plays a vital role in industries because of having plenty of beneficial impacts like low cost and easiness but the problems lik...The 3Φinduction motor is a broadly used electric machine in industrial applications,which plays a vital role in industries because of having plenty of beneficial impacts like low cost and easiness but the problems like decrease in motor speed due to load,high consumption of current and high ripple occurrence of ripples have reduced its preferences.The ultimate objective of this study is to control change in motor speed due to load variations.An improved Trans Z Source Inverter(ΓZSI)with a clamping diode is employed to maintain constant input voltage,reduce ripples and voltage overshoot.To operate induction motor at rated speed,different controllers are used.The conventional Proportional-Inte-gral(PI)controller suffers from high settling time and maximum peak overshoot.To overcome these limitations,Fractional Order Proportional Integral Derivative(FOPID)controller optimized by Gray Wolf Optimization(GWO)technique is employed to provide better performance by eliminating maximum peak overshoot pro-blems.The proposed speed controller provides good dynamic response and controls the induction motor more effectively.The complete setup is implemented in MATLAB Simulation to verify the simulation results.The proposed approach provides optimal performance with high torque and speed along with less steady state error.展开更多
This paper demonstrates the application of optimization techniques,namely the Dung Beetle Optimizer(DBO)and the Ant-Lion Optimizer(ALO),to enhance the performance of cascaded Proportional Integral Derivative(PID)and F...This paper demonstrates the application of optimization techniques,namely the Dung Beetle Optimizer(DBO)and the Ant-Lion Optimizer(ALO),to enhance the performance of cascaded Proportional Integral Derivative(PID)and Fractional Order PID(FOPID)controllers at the edge of an industrial network for Switched Reluctance Motor(SRM)speed control and torque ripple reduction.These techniques present notable advantages in terms of faster convergence and reduced computational complexity compared to existing optimization methods.Our research employs PID and FOPID controllers to regulate the speed and torque of the SRM,with a comparative analysis of other optimization approaches.In the domain of SRM control,we highlight the significance of the hysteresis band block in mitigating sudden state transitions,especially crucial for ensuring stable operation in the presence of noisy or slightly variable input signals requiring precise control.The results underscore the superior performance of the proposed optimization strategies,particularly showcasing the DBO-based cascaded PID and FOPID controllers,which exhibit reduced torque and current ripples along with improved speed response.Our investigation encompasses diverse loading conditions and is substantiated through time-domain simulations performed using MATLAB/SIMULINK.展开更多
The cohort intelligence （CI） method has recently evolved as an optimization method based on artificial intelligence. We use the CI method for the first time to optimize the parameters of the fractional proportional-...The cohort intelligence （CI） method has recently evolved as an optimization method based on artificial intelligence. We use the CI method for the first time to optimize the parameters of the fractional proportional- integral-derivative （PID） controller. The performance of the CI method in designing the fractional PID controller was validated and compared with those of some other popular algorithms such as particle swarm optimization, the genetic algorithm, and the improved electromagnetic algorithm. The CI method yielded improved solutions in terms of the cost function, computing time, and function evaluations in comparison with the other three algorithms. In addition, the standard deviations of the CI method demonstrated the robustness of the proposed algorithm in solving control problems.展开更多
基金the National Natural Science Foundation of China(Nos.61364004 and 51808275)the Chinese Scholars to Study Overseas Sponsored by ChinaScholarship Council Foundation(No.201408625045)+1 种基金the Doctoral Research Funds of Lanzhou University of Technology(No.04-237)the Alumni Foundation Civil Engineering 77,Lanzhou University of Technology(No.TM-QK1301)。
文摘The traditional integer order PID controller manipulates the air-conditioning fan coil unit(FCU)that offers cooliug and heatins loads to each air-conditioning room in summer and winter,respectivelv.In order to maintain a steady indoor temperature in summer and winter,the control quality cannot meet the related requirements of air-conditioning automation,such as large overshoot,large steady state error.long regulating time,etc.In view of these factors,this paper develops a fractional order PID controller to deal with such problem associated with FCU.Then,by varving mutation factor and crossover rate of basic differential evolution algorithmadaptivelv,a modified differential evolution algorithm(MDEA)is designed to tune the satisfactory values of five parameters of indoor temperature fractional order PID controller.This fractional order PID coutrol system is configured and the corresponding mumerical simulation is conducted by means of MATLAB software.The results indicate that the proposed fractional order PID control svstem and MDEA are reliable and the related control performance indexes meet with the related requirements of comfortable air-conditioning design and control criteria.
文摘Core power is a key parameter of nuclear reactor.Traditionally,the proportional-integralderivative(PID)controllers are used to control the core power.Fractional-order PID(FOPID)controller represents the cutting edge in core power control research.In comparing with the integer-order models,fractional-order models describe the variation of core power more accurately,thus provide a comprehensive and realistic depiction for the power and state changes of reactor core.However,current fractional-order controllers cannot adjust their parameters dynamically to response the environmental changes or demands.In this paper,we aim at the stable control and dynamic responsiveness of core power.Based on the strong selflearning ability of artificial neural network(ANN),we propose a composite controller combining the ANN and FOPID controller.The FOPID controller is firstly designed and a back propagation neural network(BPNN)is then utilized to optimize the parameters of FOPID.It is shown by simulation that the composite controller enables the real-time parameter tuning via ANN and retains the advantage of FOPID controller.
基金Supported by the Innovation Foundation of Aerospace Science and Technology(CASC200902)~~
文摘Active disturbance rejection controller（ADRC）uses tracking-differentiator（TD）to solve the contradiction between the overshoot and the rapid nature.Fractional order proportion integral derivative（PID）controller improves the control quality and expands the stable region of the system parameters.ADRC fractional order（ADRFO）PID controller is designed by combining ADRC with the fractional order PID and applied to reentry attitude control of hypersonic vehicle.Simulation results show that ADRFO PID controller has better control effect and greater stable region for the strong nonlinear model of hypersonic flight vehicle under the influence of external disturbance,and has stronger robustness against the perturbation in system parameters.
文摘In this paper,simulated and experimental results on the conical tank level control are presented.PI/PID controllers of integer order(IO)as well as of fractional order(FO)are studied and compared.The tuning parameters are obtained first by using root locus(RL)and Ziegler and Nichols methods,for comparison purposes.Next,particle swarm optimization(PSO)is employed to determine the optimal controllers'parameters using as fitness function the integral of the absolute value of tracking error(IAE).From the experimental results it is concluded that PI/FOPI are the controllers presenting the lowest IAE indexes,whereas PID/FOPID controllers present the lowest energy consumption by the control signal.
基金supported by the Board of Research in Nuclear Sciences of the Department of Atomic Energy,India(2012/36/69-BRNS/2012)
文摘The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS),which is inherently nonlinear and unstable system.The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller.An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored.The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique.Effectiveness of the proposed control scheme is verified by simulation and experimental results.The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers.It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.
文摘A new discretization scheme is proposed for the design of a fractional order PID controller. In the design of a fractional order controller the interest is mainly focused on the s-domain, but there exists a difficult problem in the s-domain that needs to be solved, i.e. how to calculate fractional derivatives and integrals efficiently and quickly. Our scheme adopts the time domain that is well suited for Z-transform analysis and digital implementation. The main idea of the scheme is based on the definition of Grünwald-Letnicov fractional calculus. In this case some limited terms of the definition are taken so that it is much easier and faster to calculate fractional derivatives and integrals in the time domain or z-domain without loss much of the precision. Its effectiveness is illustrated by discretization of half-order fractional differential and integral operators compared with that of the analytical scheme. An example of designing fractional order digital controllers is included for illustration, in which different fractional order PID controllers are designed for the control of a nonlinear dynamic system containing one of the four different kinds of nonlinear blocks: saturation, deadzone, hysteresis, and relay.
文摘3-RRR planar parallel robots are utilized for solving precise material-handling problems in industrial automation applications.Thus,robust and stable control is required to deliver high accuracy in comparison to the state of the art.The operation of the mechanism is achieved based on three revolute(3-RRR)joints which are geometrically designed using an open-loop spatial robotic platform.The inverse kinematic model of the system is derived and analyzed by using the geometric structure with three revolute joints.The main variables in our design are the platform base positions,the geometry of the joint angles,and links of the 3-RRR planar parallel robot.These variables are calcula ted based on Cayley-Menger determinants and bilateration to det ermine the final position of the platform when moving and placing objects.Additionally,a proposed fractional order proportional integral derivative(FOPID)is optimized using the bat optimization algorithm to control the path tracking of the center of the 3-RRR planar parallel robot.The design is compared with the state of the art and simulated using the Matlab environment to validate the effectiveness of the proposed controller.Furthermore,real-time implementation has been tested to prove that the design performance is practical.
文摘Interacting The highest storage capacity of a circular tank makes it pop-ular in process industries.Because of the varying surface area of the cross-sec-tions of the tank,this two-tank level system has nonlinear characteristics.Controlling theflow rate of liquid is one of the most difficult challenges in the production process.This proposed effort is critical in preventing time delays and errors by managing thefluid level.Several scholars have explored and explored ways to reduce the problem of nonlinearity,but their techniques have not yielded better results.Different types of controllers with various techniques are implemented by the proposed system.Sliding Mode Controller(SMC)with Fractional Order PID Controller based on Intelligent Adaptive Neuro-Fuzzy Infer-ence System(ANFIS)is a novel technique for liquid level regulation in an inter-connected spherical tank system to avoid interferences and achieve better performance in comparison of rise time,settling time,and overshoot decrease.Evaluating the simulated results acquired by the controller yields the efficiency of the proposed system.The simulated results were produced using MATLAB 2018 and the FOMCON toolbox.Finally,the performance of the conventional controller(FOPID,PID-SMC)and proposed ANFIS based SMC-FOPID control-lers are compared and analyzed the performance indices.
文摘Wind energy sources have different structures and functions from conventional power plants in the power system.These resources can affect the exchange of active and reactive power of the network.Therefore,power system stability will be affected by the performance of wind power plants,especially in the event of a fault.In this paper,the improvement of the dynamic stability in power system equipped by wind farm is examined through the supplementary controller design in the high voltage direct current(HVDC)based on voltage source converter(VSC)transmission system.In this regard,impacts of the VSC HVDC system and wind farm on the improvement of system stability are considered.Also,an algorithm based on controllability(observability)concept is proposed to select most appropriate and effective coupling between inputs-outputs(IO)signals of system in different work conditions.The selected coupling is used to apply damping controller signal.Finally,a fractional order PID controller(FO-PID)based on exchange market algorithm(EMA)is designed as damping controller.The analysis of the results shows that the wind farm does not directly contribute to the improvement of the dynamic stability of power system.However,it can increase the controllability of the oscillatory mode and improve the performance of the supplementary controller.
基金This research was funded by the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia through the project number“IF_2020_NBU_434”.
文摘In this study,a bald eagle optimizer(BEO)is used to get optimal parameters of the fractional-order proportional-integral-derivative(FOPID)controller for load frequency control(LFC).SinceBEOtakes only a very short time in finding the optimal solution,it is selected for designing the FOPID controller that improves the system stability and maintains the frequency within a satisfactory range at different loads.Simulations and demonstrations are carried out using MATLAB-R2020b.The performance of the BEOFOPID controller is evaluated using a two-zone interlinked power system at different loads and under uncertainty of wind and solar energies.The robustness of the BEO-FOPID controller is examined by testing its performance under varying system time constants.The results obtained by the BEOFOPID controller are compared with those obtained by BEO-PID and PID controllers based on recent metaheuristics optimization algorithms,namely the sine-cosine approach,Jaya approach,grey wolf optimizer,genetic algorithm,bacteria foraging optimizer,and equilibrium optimization algorithm.The results confirm that the BEO-FOPID controller obtains the finest result,with the lowest frequency deviation.The results also confirm that the BEOFOPID controller is stable and robust at different loads,under varying system time constants,and under uncertainty of wind and solar energies.
基金The authors extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number(IF-PSAU-2021/01/18128).
文摘In this research,a modified fractional order proportional integral derivate(FOPID)control method is proposed for the photovoltaic(PV)and thermoelectric generator(TEG)combined hybrid renewable energy system.The faster tracking and steady-state output are aimed at the suggested maximum power point tracking(MPPT)control technique.The derivative order number(μ)value in the improved FOPID(also known as PIλDμ)control structure will be dynamically updated utilizing the value of change in PV array voltage output.During the transient,the value ofμis changeable;it’s one at the start and after reaching the maximum power point(MPP),allowing for strong tracking characteristics.TEG will use the freely available waste thermal energy created surrounding the PVarray for additional power generation,increasing the system’s energy conversion efficiency.A high-gain DC-DC converter circuit is included in the system to maintain a high amplitude DC input voltage to the inverter circuit.The proposed approach’s performance was investigated using an extensive MATLAB software simulation and validated by comparing findings with the perturbation and observation(P&O)type MPPT control method.The study results demonstrate that the FOPID controller-based MPPT control outperforms the P&O method in harvesting the maximum power achievable from the PV-TEG hybrid source.There is also a better control action and a faster response.
文摘The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative(FOPID)controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration.To improve load frequency control,the proposed controllers are applied to a two-area interconnectedmicrogrid system incorporating diverse energy sources,such as wind turbines,photovoltaic cells,diesel generators,and various storage technologies.A novelmeta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers.The efficacy of the advanced FOPID controllers is demonstrated through comparative analyses against traditional proportional integral derivative(PID)and FOPID controllers,showcasing superior performance inmanaging systemfluctuations.The optimization algorithm is also evaluated against other artificial intelligent methods for parameter optimization,affirming the proposed solution’s efficiency.The robustness of the intelligent controllers against system uncertainties is further validated under extensive power disturbances,proving their capability to maintain grid stability.The dual-controller configuration ensures redundancy,allowing them to operate as mutual backups,enhancing system reliability.This research underlines the importance of sophisticated control strategies for future-proofing microgrid operations against the backdrop of evolving energy landscapes.
文摘The 3Φinduction motor is a broadly used electric machine in industrial applications,which plays a vital role in industries because of having plenty of beneficial impacts like low cost and easiness but the problems like decrease in motor speed due to load,high consumption of current and high ripple occurrence of ripples have reduced its preferences.The ultimate objective of this study is to control change in motor speed due to load variations.An improved Trans Z Source Inverter(ΓZSI)with a clamping diode is employed to maintain constant input voltage,reduce ripples and voltage overshoot.To operate induction motor at rated speed,different controllers are used.The conventional Proportional-Inte-gral(PI)controller suffers from high settling time and maximum peak overshoot.To overcome these limitations,Fractional Order Proportional Integral Derivative(FOPID)controller optimized by Gray Wolf Optimization(GWO)technique is employed to provide better performance by eliminating maximum peak overshoot pro-blems.The proposed speed controller provides good dynamic response and controls the induction motor more effectively.The complete setup is implemented in MATLAB Simulation to verify the simulation results.The proposed approach provides optimal performance with high torque and speed along with less steady state error.
文摘This paper demonstrates the application of optimization techniques,namely the Dung Beetle Optimizer(DBO)and the Ant-Lion Optimizer(ALO),to enhance the performance of cascaded Proportional Integral Derivative(PID)and Fractional Order PID(FOPID)controllers at the edge of an industrial network for Switched Reluctance Motor(SRM)speed control and torque ripple reduction.These techniques present notable advantages in terms of faster convergence and reduced computational complexity compared to existing optimization methods.Our research employs PID and FOPID controllers to regulate the speed and torque of the SRM,with a comparative analysis of other optimization approaches.In the domain of SRM control,we highlight the significance of the hysteresis band block in mitigating sudden state transitions,especially crucial for ensuring stable operation in the presence of noisy or slightly variable input signals requiring precise control.The results underscore the superior performance of the proposed optimization strategies,particularly showcasing the DBO-based cascaded PID and FOPID controllers,which exhibit reduced torque and current ripples along with improved speed response.Our investigation encompasses diverse loading conditions and is substantiated through time-domain simulations performed using MATLAB/SIMULINK.
文摘The cohort intelligence （CI） method has recently evolved as an optimization method based on artificial intelligence. We use the CI method for the first time to optimize the parameters of the fractional proportional- integral-derivative （PID） controller. The performance of the CI method in designing the fractional PID controller was validated and compared with those of some other popular algorithms such as particle swarm optimization, the genetic algorithm, and the improved electromagnetic algorithm. The CI method yielded improved solutions in terms of the cost function, computing time, and function evaluations in comparison with the other three algorithms. In addition, the standard deviations of the CI method demonstrated the robustness of the proposed algorithm in solving control problems.
