Electrohydraulic servosystem have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In order to incr...Electrohydraulic servosystem have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In order to increase the reliability, controllability and utilizing the superior speed of response achievable from electrohydraulic systems, further research is required to develop a control software has the ability of overcoming the problems of system nonlinearities. In This paper, a Proportional Integral Derivative (PID) controller is designed and attached to electrohydraulic servo actuator system to control its angular position. The PID parameters are optimized by the Genetic Algorithm (GA). The controller is verified on the state space model of servovalve attached to a rotary actuator by SIMULINK program. The appropriate specifications of the GA for the rotary position control of an actuator system are presented. It is found that the optimal values of the feedback gains can be obtained within 10 generations, which corresponds to about 200 experiments. A new fitness function was implemented to optimize the feedback gains and its efficiency was verified for control such nonlinear servosystem.展开更多
Combining with the characteristic of the fuzzy control and the neural networkcontrol(NNC), a new kind of the fuzzy neural network controller is proposed, and the synthesisdesign method of the control law and fast spee...Combining with the characteristic of the fuzzy control and the neural networkcontrol(NNC), a new kind of the fuzzy neural network controller is proposed, and the synthesisdesign method of the control law and fast speed learning algorithm of the parameters of networks areput forward. The output of the controller is composed of two parts, part one is derived on basis ofthe principle of sliding control, the lower order model and the estimated parameters of the plantare only required, part two is derived on basis FNN, it is used to compensate the uncertainties ofthe systems. Because new type of FNN controller extracts from the advantages of the intelligentcontrol and model based sliding mode control, the numbers of adjusting parameters and the structureof FNN are simplified at large, and the practical significance and variation range are attached toeach layer of the network and its connected weights, the control performance and learning speed areincreased at large. The Tightness of the conclusions is verified by the experiment of anelectro-hydraulic position servo system of the mold of the continuous casting machinery.展开更多
文摘Electrohydraulic servosystem have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In order to increase the reliability, controllability and utilizing the superior speed of response achievable from electrohydraulic systems, further research is required to develop a control software has the ability of overcoming the problems of system nonlinearities. In This paper, a Proportional Integral Derivative (PID) controller is designed and attached to electrohydraulic servo actuator system to control its angular position. The PID parameters are optimized by the Genetic Algorithm (GA). The controller is verified on the state space model of servovalve attached to a rotary actuator by SIMULINK program. The appropriate specifications of the GA for the rotary position control of an actuator system are presented. It is found that the optimal values of the feedback gains can be obtained within 10 generations, which corresponds to about 200 experiments. A new fitness function was implemented to optimize the feedback gains and its efficiency was verified for control such nonlinear servosystem.
基金This project is supported by National Natural Science Foundation of China (No.59975003).
文摘Combining with the characteristic of the fuzzy control and the neural networkcontrol(NNC), a new kind of the fuzzy neural network controller is proposed, and the synthesisdesign method of the control law and fast speed learning algorithm of the parameters of networks areput forward. The output of the controller is composed of two parts, part one is derived on basis ofthe principle of sliding control, the lower order model and the estimated parameters of the plantare only required, part two is derived on basis FNN, it is used to compensate the uncertainties ofthe systems. Because new type of FNN controller extracts from the advantages of the intelligentcontrol and model based sliding mode control, the numbers of adjusting parameters and the structureof FNN are simplified at large, and the practical significance and variation range are attached toeach layer of the network and its connected weights, the control performance and learning speed areincreased at large. The Tightness of the conclusions is verified by the experiment of anelectro-hydraulic position servo system of the mold of the continuous casting machinery.
