Research Of Adaptive Output Feed-back Control For Time-delay Nonlinear Hysteresis System

With the constant discovery and the increasingly widespread of intelligent materials,the serious influence system control precision of the intrinsic characteristics of intelligent materials-hysteresis phenomenon more and more be taken seriously;Similar to hysteresis phenomenon,time lag phenomenon is also widely exists in various kinds of unit and the actual system,it will reduce the accuracy of the system control and even make the system unstable;In the actual system,usually output is measurable,and usually has a clear physical meaning.So the output feedback of hysteresis nonlinear time-delay systems not only have abundant practical application background,has more theoretical value.For both hysteresis,time delay,nonlinear factors such as the complex nonlinear system,relying only on linear system theory and the traditional PID control method is not very good satisfy the control targets,with the deepening of the research on the adaptive control method,the method of backstepping can containing the unknown parameters,improving the quality of transition method and have obvious advantages,Based on the backstepping method,dynamic surface control method inherits the advantage of backstepping method,overcomes the drawback of backstepping method,the current widespread concern.This article put hysteresis nonlinear time-delay systems as the main object,has achieved the following results:(1)Aiming at all measurable hysteresis nonlinear time-delay systems,this paper proposes a dynamic surface control method based on RBF neural network.The main characteristic of this method is: the dynamic surface control method,greatly simplifies the controller design process;By RBF neural network to estimate the unknown time-delay function,to avoid the build are commonly used to deal with time-delay complex Krasovskii functions,to relax the assumption of time delay function,can design the controller in the case of delay function is completely unknown,improved the existing algorithm of dynamic surface;Stability analysis show that the control scheme can guarantee the control object,control law,regulation and law,etc of the closed-loop system is stable and through the selection of parameters,can make the tracking error arbitrarily small.Finally,the effectiveness of the method has been proved by the simulation.(2)In view of the only known to the system output hysteresis nonlinear time-delay systems,this paper proposes a dynamic surface control method based on RBF neural network.The main characteristic of this method is as follows: in the third chaper using dynamic surface control method,and by RBF neural network to estimate the unknown time-delay function,on the basis of in the presence of unknown state,the K-filter to estimatethe unknown state variable,realized under the condition of unknown state variable controller design;Stability analysis show that the control scheme can guarantee the stability of the closed-loop system and through the selection of parameters,can make the tracking error arbitrarily small;Finally,the effectiveness of the method has been proved by the simulation.