In accordance with the feature of pure delay in monitor AGC system for cold rolling mill, a new fuzzy selftuning PID Smith prediction controller is developed. The position control model is deduced based on a single st...In accordance with the feature of pure delay in monitor AGC system for cold rolling mill, a new fuzzy selftuning PID Smith prediction controller is developed. The position control model is deduced based on a single stand cold rolling mill, and the fuzzy controller for monitor AGC system is designed. The analysis of dynamic performance for traditional PID Smith prediction controller and fuzzy self-tuning PID Smith prediction controller is done by MAT- LAB toolbox. The simulation results show that fuzzy self-tuning PID Smith controller has stronger robustness, faster response and higher static accuracy than traditional PID Smith controller.展开更多
In this paper, a fuzzy self-tuning Proportional-Integral-Derivative (PID) control of hydrogen-driven Pneumatic Artificial Muscle (PAM) actuator is presented. With a conventional PID control, non-linear thermodynam...In this paper, a fuzzy self-tuning Proportional-Integral-Derivative (PID) control of hydrogen-driven Pneumatic Artificial Muscle (PAM) actuator is presented. With a conventional PID control, non-linear thermodynamics of the hydrogen-driven PAM actuator still highly affects the mechanical actuations itself, causing deyiation of desired tasks. The fuzzy self-tuning PID con- troller is systematically developed so as to achieve dynamic performance targets of the hydrogen-driven PAM actuator. The fuzzy rules based on desired characteristics of closed-loop control are designed to finely tune the PID gains of the controller under different operating conditions. The empirical models and properties of the hydrogen-driven PAM actuator are used as a genuine representation of mechanical actuations. A mass-spring-damper system is applied to the hydrogen-driven PAM actuator as a typical mechanical load during actuations. The results of the implementation show that the viability of the proposed method in actuating the hydrogen-driven PAM under mechanical loads is close to desired oerformance.展开更多
Fuzzy logic has attracted the attention of structural control engineers during the last few years,because fuzzy logic can handle nonlinearities,uncertainties,and heuristic knowledge effectively and easily.In this pape...Fuzzy logic has attracted the attention of structural control engineers during the last few years,because fuzzy logic can handle nonlinearities,uncertainties,and heuristic knowledge effectively and easily.In this paper,a self-Tuning fuzzy-PID control method which used the technology of the fuzzy control and PID control unified is presented.These techniques can visualize the results and processes for structure stress.These techniques will also provide convenience for engineers and users,and have high practical values.The MATLAB simulation result shows that the system precision and the efficiency are very high and the static error is small,and robustness was also validated.展开更多
In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new se...In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.展开更多
This paper presents the design and performance analysis of Differential Evolution(DE)algorithm based Proportional-Integral-Derivative(PID)controller for temperature control of Continuous Stirred Tank Reactor(CSTR)plan...This paper presents the design and performance analysis of Differential Evolution(DE)algorithm based Proportional-Integral-Derivative(PID)controller for temperature control of Continuous Stirred Tank Reactor(CSTR)plant in che-mical industries.The proposed work deals about the design of Differential Evolu-tion(DE)algorithm in order to improve the performance of CSTR.In this,the process is controlled by controlling the temperature of the liquid through manip-ulation of the coolantflow rate with the help of modified Model Reference Adap-tive Controller(MRAC).The transient response of temperature process is improved by using PID Controller,Differential Evolution Algorithm based PID and fuzzy based DE controller.Finally,the temperature response is compared with experimental results of CSTR.展开更多
Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion ...Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.展开更多
A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Co...A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Combing the traits of SMC and CSTR,three fuzzy rules can meet the requirements of controlled system.The self-tuning switch control law which can drive the state variables to the sliding surface as soon as possible is designed to ensure the robustness of uncertain fuzzy system.Lyapunov equation is applied to proving the stability of the sliding surface.The simulations show that the proposed approach can achieve desired performance with less chattering problem.展开更多
In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses an open-loop relay test, calculates the tuned parameters in an open loop mode of operation before it...In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses an open-loop relay test, calculates the tuned parameters in an open loop mode of operation before it updates controller parameters and runs the process as a closed-loop system. The controller reacts on a persistent offset error value as a result of load disturbance or a set point change. Practical results show that such a controller may be recommended to control a variety of industrial processes. A GUI was developed to facilitate control-mode selection, the setting of controller parameters, and the display of control system variables. GUI makes it possible to put the controller in manual or self-tuning mode.展开更多
Proportional, integral and derivative (PID) control strategy has been widely applied in heating systems in decades. To improve the accuracy and the robustness of PID control, self-tuning radial-basis-function neural n...Proportional, integral and derivative (PID) control strategy has been widely applied in heating systems in decades. To improve the accuracy and the robustness of PID control, self-tuning radial-basis-function neural network PID (RBF-PID) is developed and used. Even though being popular, during the control process both of PID and RBF-PID control strategy are inadequate in achieving simultaneous high energy-efficiency and good control accuracy. To address this problem, in this paper we develop and report an enhanced self-tuning radial-basis-function neural network PID (e-RBF-PID) controller. To identify the superiority of e-RBF-PID, following works are conducted and reported in this paper. Firstly, four controllers, i.e., on-off, PID, RBF-PID and e-RBF-PID are designed. Secondly, in order to test the performance of the e-RBF-PID controller, an experimental water heating system is constructed for being controlled. Finally, the energy consumption for the four controllers under the three control scenarios is investigated through experiments. The experimental results indicate that in the three scenarios, the developed e-RBF-PID controller outperforms on-off controller as having higher accuracy. Compared to the PID controller, the e-RBF-PID controller has higher speed in control, and the experimental results show that settling time savings is between 12.6% - 49.0%. Most importantly, less control energy consumption is obtained if using the e-RBF-PID controller. It is found that up to 28.5% energy consumption can be saved. Therefore, it is concluded that the proposed e-RBF-PID is capable of enhancing energy efficiency during control process.展开更多
基金Item Sponsored by National Natural Science Foundation of China (50634030)
文摘In accordance with the feature of pure delay in monitor AGC system for cold rolling mill, a new fuzzy selftuning PID Smith prediction controller is developed. The position control model is deduced based on a single stand cold rolling mill, and the fuzzy controller for monitor AGC system is designed. The analysis of dynamic performance for traditional PID Smith prediction controller and fuzzy self-tuning PID Smith prediction controller is done by MAT- LAB toolbox. The simulation results show that fuzzy self-tuning PID Smith controller has stronger robustness, faster response and higher static accuracy than traditional PID Smith controller.
文摘In this paper, a fuzzy self-tuning Proportional-Integral-Derivative (PID) control of hydrogen-driven Pneumatic Artificial Muscle (PAM) actuator is presented. With a conventional PID control, non-linear thermodynamics of the hydrogen-driven PAM actuator still highly affects the mechanical actuations itself, causing deyiation of desired tasks. The fuzzy self-tuning PID con- troller is systematically developed so as to achieve dynamic performance targets of the hydrogen-driven PAM actuator. The fuzzy rules based on desired characteristics of closed-loop control are designed to finely tune the PID gains of the controller under different operating conditions. The empirical models and properties of the hydrogen-driven PAM actuator are used as a genuine representation of mechanical actuations. A mass-spring-damper system is applied to the hydrogen-driven PAM actuator as a typical mechanical load during actuations. The results of the implementation show that the viability of the proposed method in actuating the hydrogen-driven PAM under mechanical loads is close to desired oerformance.
基金supported by Chongqing Bureau of Foreign Experts Affairs ( Project number:20075000028)
文摘Fuzzy logic has attracted the attention of structural control engineers during the last few years,because fuzzy logic can handle nonlinearities,uncertainties,and heuristic knowledge effectively and easily.In this paper,a self-Tuning fuzzy-PID control method which used the technology of the fuzzy control and PID control unified is presented.These techniques can visualize the results and processes for structure stress.These techniques will also provide convenience for engineers and users,and have high practical values.The MATLAB simulation result shows that the system precision and the efficiency are very high and the static error is small,and robustness was also validated.
基金This research is financially supported by the Ministry of Science and Technology of China(Grant No.2019YFE0112400)the Department of Science and Technology of Shandong Province(Grant No.2021CXGC011204).
文摘In this paper,a stable and adaptive sliding mode control(SMC)method for induction motors is introduced.Determining the parameters of this system has been one of the existing challenges.To solve this challenge,a new self-tuning type-2 fuzzy neural network calculates and updates the control system parameters with a fast mechanism.According to the dynamic changes of the system,in addition to the parameters of the SMC,the parameters of the type-2 fuzzy neural network are also updated online.The conditions for guaranteeing the convergence and stability of the control system are provided.In the simulation part,in order to test the proposed method,several uncertain models and load torque have been applied.Also,the results have been compared to the SMC based on the type-1 fuzzy system,the traditional SMC,and the PI controller.The average RMSE in different scenarios,for type-2 fuzzy SMC,is 0.0311,for type-1 fuzzy SMC is 0.0497,for traditional SMC is 0.0778,and finally for PI controller is 0.0997.
文摘This paper presents the design and performance analysis of Differential Evolution(DE)algorithm based Proportional-Integral-Derivative(PID)controller for temperature control of Continuous Stirred Tank Reactor(CSTR)plant in che-mical industries.The proposed work deals about the design of Differential Evolu-tion(DE)algorithm in order to improve the performance of CSTR.In this,the process is controlled by controlling the temperature of the liquid through manip-ulation of the coolantflow rate with the help of modified Model Reference Adap-tive Controller(MRAC).The transient response of temperature process is improved by using PID Controller,Differential Evolution Algorithm based PID and fuzzy based DE controller.Finally,the temperature response is compared with experimental results of CSTR.
基金Civil Project of China Aerospace Science and Technology CorporationUniversity-Industry Collaborative Education Program of Ministry of Education of China(No.220906517214433)。
文摘Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.
文摘A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Combing the traits of SMC and CSTR,three fuzzy rules can meet the requirements of controlled system.The self-tuning switch control law which can drive the state variables to the sliding surface as soon as possible is designed to ensure the robustness of uncertain fuzzy system.Lyapunov equation is applied to proving the stability of the sliding surface.The simulations show that the proposed approach can achieve desired performance with less chattering problem.
文摘In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses an open-loop relay test, calculates the tuned parameters in an open loop mode of operation before it updates controller parameters and runs the process as a closed-loop system. The controller reacts on a persistent offset error value as a result of load disturbance or a set point change. Practical results show that such a controller may be recommended to control a variety of industrial processes. A GUI was developed to facilitate control-mode selection, the setting of controller parameters, and the display of control system variables. GUI makes it possible to put the controller in manual or self-tuning mode.
文摘Proportional, integral and derivative (PID) control strategy has been widely applied in heating systems in decades. To improve the accuracy and the robustness of PID control, self-tuning radial-basis-function neural network PID (RBF-PID) is developed and used. Even though being popular, during the control process both of PID and RBF-PID control strategy are inadequate in achieving simultaneous high energy-efficiency and good control accuracy. To address this problem, in this paper we develop and report an enhanced self-tuning radial-basis-function neural network PID (e-RBF-PID) controller. To identify the superiority of e-RBF-PID, following works are conducted and reported in this paper. Firstly, four controllers, i.e., on-off, PID, RBF-PID and e-RBF-PID are designed. Secondly, in order to test the performance of the e-RBF-PID controller, an experimental water heating system is constructed for being controlled. Finally, the energy consumption for the four controllers under the three control scenarios is investigated through experiments. The experimental results indicate that in the three scenarios, the developed e-RBF-PID controller outperforms on-off controller as having higher accuracy. Compared to the PID controller, the e-RBF-PID controller has higher speed in control, and the experimental results show that settling time savings is between 12.6% - 49.0%. Most importantly, less control energy consumption is obtained if using the e-RBF-PID controller. It is found that up to 28.5% energy consumption can be saved. Therefore, it is concluded that the proposed e-RBF-PID is capable of enhancing energy efficiency during control process.
文摘针对观察型水下机器人在水下运动时易受暗流、波浪影响,造成操控困难、系统稳定性差等问题,建立遥控水下机器人(Remotely Operated Vehicle,ROV)不同运动的控制模型,考虑电机和导管螺旋桨推进器的传递函数对ROV控制系统的影响,确定定艏向和定深控制系统的闭环传递函数,结合模糊控制和比例积分微分(Proportional Integral Differential,PID)控制法,得到模糊PID控制器,基于MATLAB/Simulink环境进行ROV定深度运动仿真和ROV水平面艏向定偏角运动仿真。结果表明,与传统PID控制相比,模糊PID控制具有更优的ROV定艏向和定深度控制效果,不会发生超调现象,在抗干扰能力和响应速度方面具有明显的优势,可有效地实现ROV定艏向和定深度运动控制。