On iterative learning control design for tracking iteration-varying trajectories with high-order internal model

In this paper, iterative learning control （ILC） design is studied for an iteration-varying tracking problem in which reference trajectories are generated by high-order internal models （HOLM）. An HOlM formulated as a polynomial operator between consecutive iterations describes the changes of desired...

Full description

Saved in:
Bibliographic Details
Published in:Journal of control theory and applications 2010, Vol.8 (3), p.309-316
Main Authors: Yin, Chenkun, Xu, Jianxin, Hou, Zhongsheng
Format: Article
Language:English
Subjects:
Complexity
Computational Intelligence
Control
Control and Systems Theory
Design engineering
Engineering
Iterative methods
Learning
Mathematical models
Mechatronics
Norms
Optimization
Robotics
Systems Theory
Tracking
Trajectories
Unity
内部模型
参考轨迹
控制设计
跟踪问题
连续时间
迭代学习控制
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, iterative learning control （ILC） design is studied for an iteration-varying tracking problem in which reference trajectories are generated by high-order internal models （HOLM）. An HOlM formulated as a polynomial operator between consecutive iterations describes the changes of desired trajectories in the iteration domain and makes the iterative learning problem become iteration varying. The classical ILC for tracking iteration-invariant reference trajectories, on the other hand, is a special case of HOlM where the polynomial renders to a unity coefficient or a special first-order internal model. By inserting the HOlM into P-type ILC, the tracking performance along the iteration axis is investigated for a class of continuous-time nonlinear systems. Time-weighted norm method is utilized to guarantee validity of proposed algorithm in a sense of data-driven control.
ISSN:1672-6340
1993-0623
DOI:10.1007/s11768-010-0019-6