基于粒子群算法的控制系统PID参数优化方案设计书[1]2.docVIP

基于粒子群算法的控制系统 PID参数优化设计 摘 要 PID参数优化设计方法以及对PID控制的改进。PID参数的寻优方法有很多种，各种方法的都有各自的特点，应按实际的系统特点选择适当的方法。本文采用粒子群算法进行参数优化，主要做了如下工作：其一，，，，PID参数；其三，采用SIMULINK的仿真工具对PID参数优化系统进行仿真，得出系统的响应曲线。从中发现它的性能指标，都比原来有了很大的改进。因此，采用粒子群算法的优越性是显而易见的。 关键词 PID参数；粒子群算法；优化设计；SIMULINK Optimal design of PID parameter of the control system based on Particle Swarm Optimization Abstract The main purpose of this paper is to study the optimal design of PID parameter of the control system based on Particle Swarm Optimization and find a way to improve the PID control. There are a lot of methods of optimization for the parameters of PID, and each of them has its own characteristics. The proper methods need to be selected according to the actual characteristics of the system. In this paper we adopt the Particle Swarm Optimization to tune the parameters. To finish it, the following tasks should be done. First, select the target function of the control system. The target function of the control system should be chosen as the absolute value of the error multiplied by time. Then we simulate the control system gradually, and analyze the results of the process. Because the solution of the target function cannot be worked out directly, this design adopts simulation gradually. Second, this paper adopts the engineering method (the critical ratio method) to determine its initial parameters ,,, then uses the Particle Swarm Optimization to get a series better PID parameters. Third, this paper uses the tool of SIMULINK to optimize the parameters of PID and gets the response curve of the system. By contrast with the two response curves, it is clearly that the performance has improved a lot than the former one. Therefore, it is obviously to find the advantages in using the Particle Swarm Optimization. Key word: target function; PID parameters; Particle Swarm Optimization; optimal design; SIMULINK 目录 摘 要 I Abstract II 第1章 绪论 1 1.1 1 1.2 基本的PID参数优化方法 1 1.3 常用的整定方法 2 1.4 本文的主要工作 4 第2章 粒子群算法的介绍 5 2.1 粒子群算法思想的起源 5 2.2 算法原理 5 2.3