Over 1.3 million people die annually in traffic accidents,and this tragic fact highlights the urgent need to enhance the intelligence of traffic safety and control systems.In modern industrial and technological applic...Over 1.3 million people die annually in traffic accidents,and this tragic fact highlights the urgent need to enhance the intelligence of traffic safety and control systems.In modern industrial and technological applications and collaborative edge intelligence,control systems are crucial for ensuring efficiency and safety.However,deficiencies in these systems can lead to significant operational risks.This paper uses edge intelligence to address the challenges of achieving target speeds and improving efficiency in vehicle control,particularly the limitations of traditional Proportional-Integral-Derivative(PID)controllers inmanaging nonlinear and time-varying dynamics,such as varying road conditions and vehicle behavior,which often result in substantial discrepancies between desired and actual speeds,as well as inefficiencies due to manual parameter adjustments.The paper uses edge intelligence to propose a novel PID control algorithm that integrates Backpropagation(BP)neural networks to enhance robustness and adaptability.The BP neural network is first trained to capture the nonlinear dynamic characteristics of the vehicle.Thetrained network is then combined with the PID controller to forma hybrid control strategy.The output layer of the neural network directly adjusts the PIDparameters(k_(p),k_(i),k_(d)),optimizing performance for specific driving scenarios through self-learning and weight adjustments.Simulation experiments demonstrate that our BP neural network-based PID design significantly outperforms traditional methods,with the response time for acceleration from 0 to 1 m/s improved from 0.25 s to just 0.065 s.Furthermore,real-world tests on an intelligent vehicle show its ability to make timely adjustments in response to complex road conditions,ensuring consistent speed maintenance and enhancing overall system performance.展开更多
Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage...Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage.Although advanced PID tuning methods have been proposed,the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties.This requires continuous fine tuning of the PID parameters.However,manual adjustment of these parameters can compromise the stability and robustness of the AVR system.This study focuses on the online self-tuning of PID controllers called indirect design approach-2(IDA-2)in AVR systems while preserving robustness.In particular,we indirectly tune the PID controller by shifting the frequency response.The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters.Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously,thereby improving the control performance and robustness.We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins(GMs)and phase margins(PMs)with previously optimized PID parameters during parameter uncertainties.The proposed method is further evaluated in terms of disturbance rejection,measurement noise,and frequency response analysis during parameter uncertainty calculations against existing methods.Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system.In summary,online self-tuning enables automated PID parameter adjustment in an AVR system,while maintaining stability and robustness.展开更多
Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system ...Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.展开更多
The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and...The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process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
Aiming at the inherent blemish existi ng currently in airplane cockpit temperature regulating system,a digital temperatu re auto-regulating design scheme of the system is put forward,namely,a digita l proportional-int...Aiming at the inherent blemish existi ng currently in airplane cockpit temperature regulating system,a digital temperatu re auto-regulating design scheme of the system is put forward,namely,a digita l proportional-integral-derivative(PID) controller used for temperature contr ol is designed.And then it is applied in airpl ane cockpit temperature regulating system by adopting the way of cascade control.Experiment results indicate that the design scheme is reasonable and practical.展开更多
A proportional integral derivative （PID） controller is designed and attached to electro-hydraulic servo actuator system （EHSAS） to control the angular position of the rotary actuator which control the movable surf...A proportional integral derivative （PID） controller is designed and attached to electro-hydraulic servo actuator system （EHSAS） to control the angular position of the rotary actuator which control the movable surface of space vehicles. The PID gain parameters are optimized by the genetic algorithm （GA）. The controller is verified on the new state-space model of servo-valves attached to the physical rotary actuator by SIMULINK program. The controller and the state-space model are verified experimentally. Simulation and experimental results verify the effectiveness of the PID controller adaptive by GA to control the angular position of the rotary actuator as compared with the classical PID controller and the compensator controller.展开更多
To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID co...To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.展开更多
This paper proposes a methodology for the quantitative robustness evaluation of PID controllers employed in a DC motor. The robustness analysis is performed employing a 2~3 factorial experimental design for a fraction...This paper proposes a methodology for the quantitative robustness evaluation of PID controllers employed in a DC motor. The robustness analysis is performed employing a 2~3 factorial experimental design for a fractional order proportional integral and derivative controller(FOPID), integer order proportional integral and derivative controller(IOPID)and the Skogestad internal model control controller(SIMC). The factors assumed in experiment are the presence of random noise,external disturbances in the system input and variable load. As output variables, the experimental design employs the system step response and the controller action. Practical implementation of FOPID and IOPID controllers uses the MATLAB stateflow toolbox and a NI data acquisition system. Results of the robustness analysis show that the FOPID controller has a better performance and robust stability against the experiment factors.展开更多
The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and wi...The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.展开更多
This paper presents the application of the proportional-integral-derivative （PID） controller to the flight control system （FCS） for two-dimensional （2D） differential geometric （DG） guidance and control problem...This paper presents the application of the proportional-integral-derivative （PID） controller to the flight control system （FCS） for two-dimensional （2D） differential geometric （DG） guidance and control problem. In particular, the performance of the designed FCS is investigated. To this end, the commanded angle-of-attack is firstly developed in the time domain using the classical DG formulations. Then, the classical PID controller is introduced to develop a FCS so as to form the 2D DG guidance and control system, and the PID controller parameters are determined by the Ziegler-Nichols method as well as the Routh-Hurwitz stability algorithm to guarantee the convergence of the system error. The results demonstrate that the designed controller yields a fast responding system, and the resulting DG guidance and control system is viable and effective in a realistic missile defense engagement.展开更多
A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal ...A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.展开更多
An improved single-neuron proportional integral derivative （ PID ） controller and a new method to build the DC motor system were presented in the article. In the simulation, the robot arm is considered as an externa...An improved single-neuron proportional integral derivative （ PID ） controller and a new method to build the DC motor system were presented in the article. In the simulation, the robot arm is considered as an external load to DC motor. Both the motor module and the load module are crea- ted in Simulink to achieve simulation results closer to real robot system. In this way, it can well veri- fy the performance of the improved single-neuron PID controller, which is a combined controller of normal PID controller and single-neuron PID controller. Besides, an intelligent switcher can help to realize the function of choosing a better control algorithm according to motor＇ s velocity output. Sim- ulated results confirm the rapid and stable response of the improved PID controller. Moreover, the improved single-neuron PID controller has an excellent ability to overcome the load impact and su- press the jamming signals. At last, a GUI interface platform is built to make the controller easier to be applied in other robot systems.展开更多
The performance of the designed digital electro-pneumatic cabin pressure control system for the cabin pressure schedule of transport aircraft is investigated.For the purpose of this study,an experimental setup consist...The performance of the designed digital electro-pneumatic cabin pressure control system for the cabin pressure schedule of transport aircraft is investigated.For the purpose of this study,an experimental setup consisting of a simulated hermetic cabin and altitude simulation chamber is configured for cabin pressure control system operation.A series of experimental tests are executed to evaluate the performance of the cabin pressure control system.The parameters of the PID controller are optimized.In the optimization process,the variation regularity of the rate of cabin pressure change under various conditions is considered.An approach to prioritize the control of the rate of change of cabin pressure based on the flight status model is proposed and verified experimentally.The experimental results indicate that the proposed approach can be adopted for the designed digital electro-pneumatic cabin pressure control system to obtain a better cabin pressure schedule and rate of cabin pressure change.展开更多
An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control...An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control. Based on Lyapunov theory, Smith predictor was analyzed in time domain. The parameters of the fuzzy PID controller can be obtained using traditional linear control theory and sliding mode control theory. The simulation experiments were implemented. The simulation results show that the control performance, robustness and stability of the fuzzy PID controller are better than those of the PID controller in Smith predictor.展开更多
基金supported by the National Key Research and Development Program of China(No.2023YFF0715103)-financial supportNational Natural Science Foundation of China(Grant Nos.62306237 and 62006191)-financial support+1 种基金Key Research and Development Program of Shaanxi(Nos.2024GX-YBXM-149 and 2021ZDLGY15-04)-financial support,NorthwestUniversity Graduate Innovation Project(No.CX2023194)-financial supportNatural Science Foundation of Shaanxi(No.2023-JC-QN-0750)-financial support.
文摘Over 1.3 million people die annually in traffic accidents,and this tragic fact highlights the urgent need to enhance the intelligence of traffic safety and control systems.In modern industrial and technological applications and collaborative edge intelligence,control systems are crucial for ensuring efficiency and safety.However,deficiencies in these systems can lead to significant operational risks.This paper uses edge intelligence to address the challenges of achieving target speeds and improving efficiency in vehicle control,particularly the limitations of traditional Proportional-Integral-Derivative(PID)controllers inmanaging nonlinear and time-varying dynamics,such as varying road conditions and vehicle behavior,which often result in substantial discrepancies between desired and actual speeds,as well as inefficiencies due to manual parameter adjustments.The paper uses edge intelligence to propose a novel PID control algorithm that integrates Backpropagation(BP)neural networks to enhance robustness and adaptability.The BP neural network is first trained to capture the nonlinear dynamic characteristics of the vehicle.Thetrained network is then combined with the PID controller to forma hybrid control strategy.The output layer of the neural network directly adjusts the PIDparameters(k_(p),k_(i),k_(d)),optimizing performance for specific driving scenarios through self-learning and weight adjustments.Simulation experiments demonstrate that our BP neural network-based PID design significantly outperforms traditional methods,with the response time for acceleration from 0 to 1 m/s improved from 0.25 s to just 0.065 s.Furthermore,real-world tests on an intelligent vehicle show its ability to make timely adjustments in response to complex road conditions,ensuring consistent speed maintenance and enhancing overall system performance.
基金the Malaysian Ministry of Higher Education(MOHE)for their support through the Fundamental Research Grant Scheme(FRGS/1/2021/ICT02/UMP/03/3)(UMPSA Reference:RDU 210117)。
文摘Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage.Although advanced PID tuning methods have been proposed,the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties.This requires continuous fine tuning of the PID parameters.However,manual adjustment of these parameters can compromise the stability and robustness of the AVR system.This study focuses on the online self-tuning of PID controllers called indirect design approach-2(IDA-2)in AVR systems while preserving robustness.In particular,we indirectly tune the PID controller by shifting the frequency response.The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters.Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously,thereby improving the control performance and robustness.We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins(GMs)and phase margins(PMs)with previously optimized PID parameters during parameter uncertainties.The proposed method is further evaluated in terms of disturbance rejection,measurement noise,and frequency response analysis during parameter uncertainty calculations against existing methods.Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system.In summary,online self-tuning enables automated PID parameter adjustment in an AVR system,while maintaining stability and robustness.
文摘Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.
基金the Key Technologies R&D Program of Harbin (0111211102).
文摘The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process
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Aiming at the inherent blemish existi ng currently in airplane cockpit temperature regulating system,a digital temperatu re auto-regulating design scheme of the system is put forward,namely,a digita l proportional-integral-derivative(PID) controller used for temperature contr ol is designed.And then it is applied in airpl ane cockpit temperature regulating system by adopting the way of cascade control.Experiment results indicate that the design scheme is reasonable and practical.
文摘A proportional integral derivative （PID） controller is designed and attached to electro-hydraulic servo actuator system （EHSAS） to control the angular position of the rotary actuator which control the movable surface of space vehicles. The PID gain parameters are optimized by the genetic algorithm （GA）. The controller is verified on the new state-space model of servo-valves attached to the physical rotary actuator by SIMULINK program. The controller and the state-space model are verified experimentally. Simulation and experimental results verify the effectiveness of the PID controller adaptive by GA to control the angular position of the rotary actuator as compared with the classical PID controller and the compensator controller.
基金the National Natural Science Foundation of China (60375001)the Scientific Research Foundation of Hunan Provincial Education Department (05B016).
文摘To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.
文摘This paper proposes a methodology for the quantitative robustness evaluation of PID controllers employed in a DC motor. The robustness analysis is performed employing a 2~3 factorial experimental design for a fractional order proportional integral and derivative controller(FOPID), integer order proportional integral and derivative controller(IOPID)and the Skogestad internal model control controller(SIMC). The factors assumed in experiment are the presence of random noise,external disturbances in the system input and variable load. As output variables, the experimental design employs the system step response and the controller action. Practical implementation of FOPID and IOPID controllers uses the MATLAB stateflow toolbox and a NI data acquisition system. Results of the robustness analysis show that the FOPID controller has a better performance and robust stability against the experiment factors.
基金Project(51090385) supported by the Major Program of National Natural Science Foundation of ChinaProject(2011IB001) supported by Yunnan Provincial Science and Technology Program,China+1 种基金Project(2012DFA70570) supported by the International Science & Technology Cooperation Program of ChinaProject(2011IA004) supported by the Yunnan Provincial International Cooperative Program,China
文摘The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.
基金Throughout this paper, the word velocity will only be used to designate a vector quantitythe corresponding scalar will be denoted asspeed
文摘This paper presents the application of the proportional-integral-derivative （PID） controller to the flight control system （FCS） for two-dimensional （2D） differential geometric （DG） guidance and control problem. In particular, the performance of the designed FCS is investigated. To this end, the commanded angle-of-attack is firstly developed in the time domain using the classical DG formulations. Then, the classical PID controller is introduced to develop a FCS so as to form the 2D DG guidance and control system, and the PID controller parameters are determined by the Ziegler-Nichols method as well as the Routh-Hurwitz stability algorithm to guarantee the convergence of the system error. The results demonstrate that the designed controller yields a fast responding system, and the resulting DG guidance and control system is viable and effective in a realistic missile defense engagement.
基金This work was supported by the National Natural Science Foundation of China (No. 50275150)the Foundation of Robotics Laboratory, Chinese Academy of Sciences( No. RL200002).
文摘A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.
文摘An improved single-neuron proportional integral derivative （ PID ） controller and a new method to build the DC motor system were presented in the article. In the simulation, the robot arm is considered as an external load to DC motor. Both the motor module and the load module are crea- ted in Simulink to achieve simulation results closer to real robot system. In this way, it can well veri- fy the performance of the improved single-neuron PID controller, which is a combined controller of normal PID controller and single-neuron PID controller. Besides, an intelligent switcher can help to realize the function of choosing a better control algorithm according to motor＇ s velocity output. Sim- ulated results confirm the rapid and stable response of the improved PID controller. Moreover, the improved single-neuron PID controller has an excellent ability to overcome the load impact and su- press the jamming signals. At last, a GUI interface platform is built to make the controller easier to be applied in other robot systems.
文摘The performance of the designed digital electro-pneumatic cabin pressure control system for the cabin pressure schedule of transport aircraft is investigated.For the purpose of this study,an experimental setup consisting of a simulated hermetic cabin and altitude simulation chamber is configured for cabin pressure control system operation.A series of experimental tests are executed to evaluate the performance of the cabin pressure control system.The parameters of the PID controller are optimized.In the optimization process,the variation regularity of the rate of cabin pressure change under various conditions is considered.An approach to prioritize the control of the rate of change of cabin pressure based on the flight status model is proposed and verified experimentally.The experimental results indicate that the proposed approach can be adopted for the designed digital electro-pneumatic cabin pressure control system to obtain a better cabin pressure schedule and rate of cabin pressure change.
基金Project(70473068) supported by the National Natural Science Foundation of ChinaProject(05JZD00024) supported by the Major Subject of Ministry of Education, China
文摘An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control. Based on Lyapunov theory, Smith predictor was analyzed in time domain. The parameters of the fuzzy PID controller can be obtained using traditional linear control theory and sliding mode control theory. The simulation experiments were implemented. The simulation results show that the control performance, robustness and stability of the fuzzy PID controller are better than those of the PID controller in Smith predictor.
