A fast PID type parameter optimal iterative learning control algorithm for non-positive plants

	A fast PID type parameter optimal iterative learning control algorithm for non-positive plants
	Li, Hengjie; Hao, Xiaohong
	2010
会议录名称	Proceedings of the 29th Chinese Control Conference, CCC'10
页码	2091-2096
出版者	IEEE Computer Society
摘要	In order to obtain faster and more accuracy transient tracking performances for non-positive plants, a fast proportional integral difference (PID) type parameter optimal iterative learning control algorithm is proposed. In the algorithm, the PID type operators are introduced to enhance convergence speed and a suitable set of basis functions is added to avoid the algorithm plunge into local optimal when the plant is not positive. Theoretic proof shows that the algorithm monotone convergence to zero no matter the system plant is positive or not. Finally, simulations show that the algorithm also has a faster convergence speed compare with other similar algorithms.
关键词	Iterative methods Parameter estimation Proportional control systems Two term control systems Convergence speed Faster convergence Iterative learning control Iterative learning control algorithm Monotone convergence Optimal Proportional integral Tracking performance
收录类别	EI
语种	英语
EI入藏号	20105113504318
EI主题词	Learning algorithms
来源库	Compendex
分类代码	731.1 Control Systems - 921.6 Numerical Methods
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/116130
专题	电气工程与信息工程学院
作者单位	School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu 730050, China
第一作者单位	兰州理工大学
推荐引用方式 GB/T 7714	Li, Hengjie,Hao, Xiaohong. A fast PID type parameter optimal iterative learning control algorithm for non-positive plants[C]:IEEE Computer Society,2010:2091-2096.