Neural Network Adaptive Predictive Performance Control For A Class Of Strictly Feedback Nonlinear Switched Systems

With the continuous improvement of industrial control precision,the demand for control performance in engineering operation is gradually increasing at present.Therefore,there are many literatures to provide corresponding theoretical research for the state design simulation of industrial process under complicated conditions.As a kind of complex system,switching systems contain many factors and their "switching" factors themselves are widely used in industrial engineering systems.Nearly forty years of related research have drawn much attention to the control design of switching systems.As one of the hot topics of theoretical research,the design of switching system control inputs and the exploration of switching rules are all the important parts of scholars' thinking and research.At present,the research methods of switching systems focus on the application of the Lyapunov function method and the dwell time method.In this paper,we apply the common Lyapunov function and the dwell time method to the application of the preset performance conversion error function,so as to carry out the following research:First,the design of the default performance controller with strict feedback nonlinear switchin 0g system under arbitrary switching is achieved by using Backstepping technique and the common Lyapunov function to complete the overall control stability of the switching system,while ensuring the error in the set transition interval Inside.In this paper,the design of switching system,the design of the default performance,the introduction of a new conversion error,the existing literature to reduce the error function set to meet the needs of the system to ensure that the steady-state and transient performance requirements.Secondly,by introducing perturbation term into the above strict feedback system,the robust controller is designed to determine and guarantee the conversion performance error function designed by the system through the common Lyapunov function,while meeting the robust characteristics of the system,Which theoretically proves that the switching system is eventually gradual and stable,and at the same time is capable of offsetting certain interference signals.Thirdly,the strict feedback nonlinear switching system is researched.When the system controller is designed,the radial basis function and the time-resident method of neural network are introduced to relax the requirements of the system.By approximating unknown items,the system states Equations in equation design needs.By referring to the conversion error function,a system controller with tracking performance is designed,and the stability of the switching system is finally completed.In this paper,we verify the rationality of the performance conversion error function in the nonlinear switching system through the research and design of the above systems of different nature to meet the steady-state and transient performance requirements of the nonlinear switching system.