Research On Control Technology Of A Certain Deep Electro-hydraulic Servo System Based On Neural Network

This study takes the application of fixed-depth electro-hydraulic servo control systems as the background,and aims to improve system reliability and control performance in complex working environments.The focus is on the perturbation and uncertainty of the internal parameters of the fixed-depth electro-hydraulic servo system,and the anti-interference of the control system to the external load disturbance.A neural network-based PID control strategy and a sliding mode variable structure control strategy were studied.This study first analyzes the structure and working principle of the fixed depth electro-hydraulic servo system,and introduces the selection of important mechanical components.On this basis,the dynamic characteristics of the system are analyzed and its mathematical model is constructed.In addition,the non-linear factors affecting the control performance of the fixed-depth electro-hydraulic servo system are analyzed in detail.Aiming at the non-linear factors in the fixed-depth electro-hydraulic servo system,a control method based on RBF neural network self-tuning PID parameters was designed.Among them,the RBF neural network is used to provide the Jacobian information of the system,and then based on this information,the three parameters of PID control are adjusted online using the gradient descent method to improve the control performance of the system.In order to improve the recognition of RBF neural network,the particle swarm optimization algorithm was used to optimize it.Simulation results show that the RBF-PID controller using particle swarm optimization has better robustness,and can effectively reduce the influence of system parameter perturbation and external load disturbance.Then,a sliding mode variable structure control method based on parameter identification of RBF neural network system is proposed.In order to suppress chattering in sliding mode variable structure control,RBF neural network is used in this strategy to approximate the nonlinear term in equivalent control.In order to speed up the response of sliding mode control and solve the chattering problem when the sliding mode motion reaches a steady state,a new sliding mode switching control law is used in this paper.The simulation results show that the RBF-SMC controller using the new switching control rate has better response performance and robustness,and can effectively suppress the occurrence of chattering.Finally,the control software is designed,and the correctness of the control strategy designed in this paper is verified by MATLAB simulation and experimental research.