一种基于LS-SVM与PID复合的逆控制系统

作者：黄银蓉，张绍德,季民 日期：2010-03-26/span> 浏览：3694 查看PDF文档

一种基于LS-SVM与PID复合的逆控制系统

黄银蓉，张绍德,季民
（安徽工业大学 电气信息学院，安徽 马鞍山 243002）

摘要：针对逆系统中非线性逆模型辨识困难的问题，研究了基于最小二乘支持向量机（LS-SVM）的逆模型辨识及控制，并用微粒子群算法（PSO）优化LS-SVM的参数和核函数参数。提出了一种由LS-SVM的逆模型与PID结合的复合控制系统,由LS-SVM辨识非线性系统的逆模型作为前馈控制器,形成直接逆控制。同时,由PID控制器构成反馈控制,克服直接逆控制鲁棒性不强的缺陷。仿真研究结果表明LS-SVM的逆模型辨识能力强，该复合控制系统具有比基于最近邻聚类的RBF神经网络逆控制系统更优的动态跟踪性能，更好的抗干扰能力和鲁棒性。
关键词：逆模型辨识；最小二乘支持向量机；微粒子群算法；逆控制
中图分类号：TP18文献标识码：A文章编号：1001-4551(2010)02-0075-04

A inverse control system based on least squares
support vector machine and PID
HUANG Yin-rong, ZHANG Shao-de, JI Min
(School of Electrical Engineering&Information, Anhui University of Technology, Maanshan 243002, China)
Abstract: Aiming at the problems of the inverse model identification in inverse system method, the realization of inverse system identification and control using least squares support vector machine(LS-SVM) were studied. A methodology, based on particle swarm optimization algorithm(PSO), for parameters selection of least squares support vector machine was proposed. A compound control strategy combing LS-SVM inverse system with PID controller was proposed. LS-SVM was used to identify the inverse model of nonlinear system, and this inverse model was used as feed-forward controller to design direct inverse control. Moreover, PID controller was used to realize feed-back control, which could overcome the limits of direct inverse control in performance and robustness. Simulation results demonstrate that LS-SVM has a good approximate capability for inverse model, and the proposed compound control system has better dynamic track performance, resistance to disturbance of system and robustness than RBF neural network.
Key words:  inverse model identification; least squares support vector machine(LS-SVM); particle swarm optimization algorithm(PSO); inverse control
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