Intelligent PID Controller Design with Adaptive Criterion Adjustment via Least Squares Support Vector Machine

摘要：

PID controllers have been widely used in many industries. They can provide robust and reliable performance for most systems. However, it is very important to tune the PID parameters properly. There is a large variety of methods for tuning the PID parameters. But none of them can cope with the wide system uncertainties. The main motivation in this paper is to present a design scheme of controllers using the LS-SVM which achieve to self-tune the parameter. This method used LS-SVM to identify the predictive model of the system off-line, then linearized the model in local on-line for reducing computation, and combined the general minimum variance to self-tune the PID parameters. The controller has a better effect than the conventional PID controller. Simulation study shows the effectiveness and good performance.

关键词： PID control Predictive model Self-tune Support Vector Machine

作者: Jun ZHAO Ping LI Xue-song WANG

作者单位: School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou The State Key Laboratory of Control Technology,Zhejiang University, Hangzhou 310027,China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 7-12

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）