Research On Neural Network Adaptive Backstepping Control Method Based On Prescribed Performance

In recent decades,the comprehensive development of control theory has provided corresponding theoretical support for various industrial control processes.However,with the rapid development of science and technology,the accused objects are becoming more and more complex,and the requirements for control quality are getting higher and higher.However,most of the existing nonlinear control strategies focus on improving the steady-state performance of the control system,but seldom consider the transient performance of the control system.In response to this problem,this paper combines the prescribed performance control with the backstepping method and other control algorithms to carry out related research.The specific research content of this paper is as follows:(1)In view of the problem that the existing nonlinear control strategy cannot improve the transient performance of the system,the prescribed performance control is introduced,and the principle and implementation method of the prescribed performance control are introduced.(2)For a specific nonlinear system with external unknown disturbance(ship trajectory tracking system),an adaptive backstepping disturbance rejection control method based on prescribed performance is proposed in this paper.The output error of the system is constrained by using the performance function with constraints,and then the error is converted by mathematical methods,and the conversion error is substituted into the backstepping method to design the controller to quantitatively design the steady-state and transient performance of the control system.The disturbance observer is designed for a specific nonlinear system,and t he disturbance observer is used to estimate the unknown external disturbance and compensate it accurately in the control law.At the same time,the adaptive law is used to estimate the bound of the disturbance observation error,and the disturbance rejecti on control with the prescribed performance of the specific nonlinear system is realized.The control algorithm is simulated and verified on MATLAB,which further proves the validity and engineering significance of the control algorithm.(3)For a specific nonlinear system with model parameter perturbation and external unknown disturbance at the same time(ship trajectory tracking system),a neural network sliding mode adaptive control method based on prescribed performance is proposed in this paper.By using the performance function with constraints to constrain the output error of the system,and then using the mathematical method to convert the error,substituting the conversion error into the sliding mode control method to design the controller to quantitativ ely design the steady-state and transient performance of the control system.Then a low-pass filter is introduced to solve the differential explosion problem,and the radial basis function neural network is used to overcome the perturbation of the model pa rameters.At the same time,the adaptive law is used to estimate the boundary of the sum of the external disturbance and the approximation error of the neural network model parameters,and the control law is further optimized,which achieves robust control of prescribed performance for specific nonlinear systems.The control algorithm is simulated and verified on MATLAB,which further proves the validity and engineering significance of the control algorithm.