Monotonic convergent iterative learning controller design based on interval model conversion

被引：0

作者：

Ahn, HS ^{[1
]}

Moore, KL ^{[1
]}

Chen, YQ ^{[1
]}

机构：

[1] Utah State Univ, CSOIS, Dept Elect & Comp Engn, Logan, UT 84322 USA

来源：

2005 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL & 13TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1 AND 2 | 2005年

关键词：

iterative learning control; interval conversion; matrix perturbation; monotonic convergence;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents the design of a robust iterative learning controller for the case of a plant with interval model uncertainty in the "A-matrix of its state space description. First order perturbation theory is utilized to find bounds on the eigenvalues and eigenvectors of the powers of A when A is an interval matrix. These bounds are then used for calculation of the interval uncertainty of the Markov matrix, which can then be used to design an iterative learning controller that ensures monotonic convergence for all systems in the interval plant.

引用

页码：1207 / 1212

页数：6

共 12 条

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[5] Moore K. L., 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304), P270, DOI 10.1109/CDC.1999.832787
[6] Moore KL, 2003, P AMER CONTR CONF, P3644
[7] Moore KL, 1999, APPL COMPUT CONT SIG, V1, P151
[8] Moore KL, 1998, IEEE DECIS CONTR P, P666, DOI 10.1109/CDC.1998.760760
[9] MOORE KL, 2002, INVITED SESSION HIGH
[10] MOORE KL, 1993, ADV IND CONTORL

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