某定深电液伺服系统的粒子群优化神经网络PID 控制

为解决定深电液伺服系统的系统参数难以确定、运行过程中内部参数具有时变性和外部负载扰动较大等问题，设计一种将PID 控制器与神经网络相结合的控制策略。分析定深电液伺服系统的数学模型和控制器的结构与工作原理，用径向基函数神经网络来动态修正PID 控制器中控制参数的策略，采用粒子群算法离线选取最优的神经网络权值，用Matlab 将控制器应用于定深电液伺服系统中，并与经典的PID 控制器和RBF-PID 控制器进行对比。仿真结果表明，该控制器具有较好的快速响应能力与鲁棒性。

PID Control of Particle Swarm Optimization Neural Network forCertain Deep Electro-hydraulic Servo System

In order to solve the problems that the system parameters of the deep electro-hydraulic servo system aredifficult to determine, the internal parameters have time-varying and the external load disturbance is large, a controlstrategy combining the PID controller and the neural network is designed. Analyze the mathematical model of the deepelectro-hydraulic servo system and the structure and working principle of the controller. The radical basis function neuralnetwork is used to dynamically modify the control parameters of the PID controller. The particle swarm algorithm is used toselect the optimal neural network right offline. Use Matlab in controller of certain deep electro-hydraulic servo system, andcompare it with the classic PID controller and RBF-PID controller. The simulation results show that the controller has goodfast response capability and robustness.