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
A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As t...A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.展开更多
Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful...Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful in overcoming non-linear dynamic behavior, uncertain and time-varying parameters, un-modeled dynamics, and couples between the automatic turbulence control (ATC) and the automatic acid temperature control (AATC) with varying parameters during the operation process. The quasi-cascade control system of inner and outer loop self-adaptive fuzzy PID controller was built, which could effectively control the pickling speed of plates and strips. The simulated results and real application indicate that the plates and strips acid pickling speed control system has good performances of adaptively tracking the parameter variations and anti-disturbances, which ensures the match of acid pickling temperature and turbulence of flowing with acid pickling speed, improving the surface quality of plates and strips acid pickling, and energy efficiency.展开更多
A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustab...A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors x p, x i , and x d are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.展开更多
A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller...A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.展开更多
Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scal...Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.展开更多
This paper presented PSS （Power system stabilizer） design based on Genetic Algorithm - Fuzzy PID （Proportional Integral and derivative） or GAFPID. GAFPID based PSS design is considered for multimachine power syste...This paper presented PSS （Power system stabilizer） design based on Genetic Algorithm - Fuzzy PID （Proportional Integral and derivative） or GAFPID. GAFPID based PSS design is considered for multimachine power system. The main motivation for this design is to stabilize or to control low-fi＇equency oscillation and terminal voltage of power systems. Genetic Algorithm （GA） is employed for the optimization of the parameter of stabilizer. By minimizing an objective function in which the oscillatory speed deviation of the generator, small signal and large signal performance of the system is improved. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a simple two-area power system.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A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.
基金Project(51090385) supported by the National Natural Science Foundation of ChinaProject(2001IB001) supported by Yunnan Provincial Science and Technology Fund, China
文摘Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful in overcoming non-linear dynamic behavior, uncertain and time-varying parameters, un-modeled dynamics, and couples between the automatic turbulence control (ATC) and the automatic acid temperature control (AATC) with varying parameters during the operation process. The quasi-cascade control system of inner and outer loop self-adaptive fuzzy PID controller was built, which could effectively control the pickling speed of plates and strips. The simulated results and real application indicate that the plates and strips acid pickling speed control system has good performances of adaptively tracking the parameter variations and anti-disturbances, which ensures the match of acid pickling temperature and turbulence of flowing with acid pickling speed, improving the surface quality of plates and strips acid pickling, and energy efficiency.
文摘A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors x p, x i , and x d are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.
文摘A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject(05JJ40128) supported by the Natural Science Foundation of Hunan Province, China
文摘Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.
文摘This paper presented PSS （Power system stabilizer） design based on Genetic Algorithm - Fuzzy PID （Proportional Integral and derivative） or GAFPID. GAFPID based PSS design is considered for multimachine power system. The main motivation for this design is to stabilize or to control low-fi＇equency oscillation and terminal voltage of power systems. Genetic Algorithm （GA） is employed for the optimization of the parameter of stabilizer. By minimizing an objective function in which the oscillatory speed deviation of the generator, small signal and large signal performance of the system is improved. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a simple two-area power system.
