A Simplified Grey Wolf Optimizer(SGWO)is suggested for resolving optimization tasks.The simplification in the original Grey Wolf Optimizer(GWO)method is introduced by ignoring the worst category wolves while giving pr...A Simplified Grey Wolf Optimizer(SGWO)is suggested for resolving optimization tasks.The simplification in the original Grey Wolf Optimizer(GWO)method is introduced by ignoring the worst category wolves while giving priority to the better wolves during the search process.The advantage of the presented SGWO over GWO is a better solution taking less execution time and is demonstrated by taking unimodal,multimodal,and fixed dimension test functions.The results are also contrasted to the Gravitational Search Algorithm,the Particle Swarm Optimization,and the Sine Cosine Algorithm and this shows the superiority of the proposed SGWO technique.Practical application in a Distributed Power Generation System(DPGS)with energy storage is then considered by designing an Adaptive Fuzzy PID(AFPID)controller using the suggested SGWO method for frequency control.The DPGS contains renewable generation such as photovoltaic,wind,and storage elements such as battery and flywheel,in addition to plug-in electric vehicles.It is demonstrated that the SGWO method is superior to the GWO method in the optimal controller design task.It is also seen that SGWO based AFPID controller is highly efficacious in regulating the frequency compared to the standard PID controller.A sensitivity study is also performed to examine the impact of the unpredictability in the parameters of the investigated system on system performance.Finally,the novelty of the paper is demonstrated by comparing with the existing publications in an extensively used two-area test system.展开更多
As a nonlinear,strong coupling and multi-variable system,the drive performance of bearingless switched reluctance motor(BLSRM)is always limited by its complicated electromagnetic properties.Generally,conventional PID ...As a nonlinear,strong coupling and multi-variable system,the drive performance of bearingless switched reluctance motor(BLSRM)is always limited by its complicated electromagnetic properties.Generally,conventional PID methods are used to achieve the basic control requirement in wide industrial applications,however its inherent operating principle limits its use on suspending control of BLSRM.In this paper,the suspending force system,which is separately controlled from torque system,is built based on an adaptive fuzzy PID controller to limit the rotor eccentric displacement with proper generation of radial force.When compared with a system adopted using conventional PID method for suspending force control,the proposed adaptive fuzzy PID method has superior performance in shortening the response time,reducing the maximum eccentric displacement error and higher speed range of operation due to its online self-turning of controller parameters.Both in simulation and experimental cases,comparison of results of the above two methods validates the effectiveness of the adaptive fuzzy PID controller for BLSRM drive system.展开更多
In order to overcome the shortcomings of the traditional sling suspension method,such as complex structure of suspension truss,large running resistance,and low precision of position servo system,a gravity compensation...In order to overcome the shortcomings of the traditional sling suspension method,such as complex structure of suspension truss,large running resistance,and low precision of position servo system,a gravity compensation method of lunar rover based on the combination of active suspension and active position following of magnetic levitation is proposed,and the overall design is carried out.The dynamic model of the suspension module of microgravity compensation system was established,and the decoupling control between the constant force component and the position servo component was analyzed and verified.The constant tension control was achieved by using hybrid force/position control.The position following control was realized by using fuzzy adaptive PID(proportional⁃integral⁃differential)control.The stable suspension control was realized based on the principle of force balance.The simulation results show that the compensation accuracy of constant tension could reach more than 95%,the position deviation was less than 5 mm,the position deviation angle was less than 0.025°,and the air gap recovered stability within 0.1 s.The gravity compensation system has excellent dynamic performance and can meet the requirements of microgravity simulation experiment of lunar rover.展开更多
This paper discusses dynamic characteristics of proton exchange membrane fuel cell (PEMFC) under rapid fluctuation of power demand. Wavelet neural network is adopted in the identification of the characteristic curve t...This paper discusses dynamic characteristics of proton exchange membrane fuel cell (PEMFC) under rapid fluctuation of power demand. Wavelet neural network is adopted in the identification of the characteristic curve to predict the voltage. The system control scheme of the voltage and power is introduced. The corresponding schemes for voltage and power control are studied. MATLAB is used to simulate the control system. The results reveal that the adopted control schemes can produce expected effects. Corresponding anti-disturbance and robustness simulation are also carried out. The simulation results show that the implemented control schemes have better robustness and adaptability.展开更多
At present,the attitude control method of plant protection UAV is the classical PID control,but there are some imperfections in the PID control,such as the contradiction between speediness and overshoot,the weak anti-...At present,the attitude control method of plant protection UAV is the classical PID control,but there are some imperfections in the PID control,such as the contradiction between speediness and overshoot,the weak anti-jamming ability and adaptability.The physical parameters of plant protection UAV are time-varying,and the airflow also interferes with it.The control ability of classical PID is limited,and its control parameters are fixed,and its anti-jamming ability and adaptability are not strong.Therefore,a fuzzy adaptive PID controller is proposed in this paper.Fuzzy logic control is used to optimize the control parameters of PID in order to improve the dynamic and static performance and adaptability of attitude control of plant protection UAV.In the process of research,the mathematical model of UAV is established firstly,then the fuzzy adaptive PID is designed,and then the simulation is carried out in Simulink.The simulation results show that the fuzzy adaptive PID controller has better dynamic and static control performance and adaptability than the traditional PID controller.Therefore,the proposed control method has excellent application value in the attitude of plant protection UAV.展开更多
文摘A Simplified Grey Wolf Optimizer(SGWO)is suggested for resolving optimization tasks.The simplification in the original Grey Wolf Optimizer(GWO)method is introduced by ignoring the worst category wolves while giving priority to the better wolves during the search process.The advantage of the presented SGWO over GWO is a better solution taking less execution time and is demonstrated by taking unimodal,multimodal,and fixed dimension test functions.The results are also contrasted to the Gravitational Search Algorithm,the Particle Swarm Optimization,and the Sine Cosine Algorithm and this shows the superiority of the proposed SGWO technique.Practical application in a Distributed Power Generation System(DPGS)with energy storage is then considered by designing an Adaptive Fuzzy PID(AFPID)controller using the suggested SGWO method for frequency control.The DPGS contains renewable generation such as photovoltaic,wind,and storage elements such as battery and flywheel,in addition to plug-in electric vehicles.It is demonstrated that the SGWO method is superior to the GWO method in the optimal controller design task.It is also seen that SGWO based AFPID controller is highly efficacious in regulating the frequency compared to the standard PID controller.A sensitivity study is also performed to examine the impact of the unpredictability in the parameters of the investigated system on system performance.Finally,the novelty of the paper is demonstrated by comparing with the existing publications in an extensively used two-area test system.
文摘As a nonlinear,strong coupling and multi-variable system,the drive performance of bearingless switched reluctance motor(BLSRM)is always limited by its complicated electromagnetic properties.Generally,conventional PID methods are used to achieve the basic control requirement in wide industrial applications,however its inherent operating principle limits its use on suspending control of BLSRM.In this paper,the suspending force system,which is separately controlled from torque system,is built based on an adaptive fuzzy PID controller to limit the rotor eccentric displacement with proper generation of radial force.When compared with a system adopted using conventional PID method for suspending force control,the proposed adaptive fuzzy PID method has superior performance in shortening the response time,reducing the maximum eccentric displacement error and higher speed range of operation due to its online self-turning of controller parameters.Both in simulation and experimental cases,comparison of results of the above two methods validates the effectiveness of the adaptive fuzzy PID controller for BLSRM drive system.
基金the National Natural Science Foundation of China(Grant Nos.51305384 and 52075466)。
文摘In order to overcome the shortcomings of the traditional sling suspension method,such as complex structure of suspension truss,large running resistance,and low precision of position servo system,a gravity compensation method of lunar rover based on the combination of active suspension and active position following of magnetic levitation is proposed,and the overall design is carried out.The dynamic model of the suspension module of microgravity compensation system was established,and the decoupling control between the constant force component and the position servo component was analyzed and verified.The constant tension control was achieved by using hybrid force/position control.The position following control was realized by using fuzzy adaptive PID(proportional⁃integral⁃differential)control.The stable suspension control was realized based on the principle of force balance.The simulation results show that the compensation accuracy of constant tension could reach more than 95%,the position deviation was less than 5 mm,the position deviation angle was less than 0.025°,and the air gap recovered stability within 0.1 s.The gravity compensation system has excellent dynamic performance and can meet the requirements of microgravity simulation experiment of lunar rover.
文摘This paper discusses dynamic characteristics of proton exchange membrane fuel cell (PEMFC) under rapid fluctuation of power demand. Wavelet neural network is adopted in the identification of the characteristic curve to predict the voltage. The system control scheme of the voltage and power is introduced. The corresponding schemes for voltage and power control are studied. MATLAB is used to simulate the control system. The results reveal that the adopted control schemes can produce expected effects. Corresponding anti-disturbance and robustness simulation are also carried out. The simulation results show that the implemented control schemes have better robustness and adaptability.
基金This research work was supported by Project of Scientific Operating Expenses from Ministry of Education of China(2017PT19)National Natural Science Foundation of China(31761133019).
文摘At present,the attitude control method of plant protection UAV is the classical PID control,but there are some imperfections in the PID control,such as the contradiction between speediness and overshoot,the weak anti-jamming ability and adaptability.The physical parameters of plant protection UAV are time-varying,and the airflow also interferes with it.The control ability of classical PID is limited,and its control parameters are fixed,and its anti-jamming ability and adaptability are not strong.Therefore,a fuzzy adaptive PID controller is proposed in this paper.Fuzzy logic control is used to optimize the control parameters of PID in order to improve the dynamic and static performance and adaptability of attitude control of plant protection UAV.In the process of research,the mathematical model of UAV is established firstly,then the fuzzy adaptive PID is designed,and then the simulation is carried out in Simulink.The simulation results show that the fuzzy adaptive PID controller has better dynamic and static control performance and adaptability than the traditional PID controller.Therefore,the proposed control method has excellent application value in the attitude of plant protection UAV.