Spatial iterative learning control for a class of uncertain motion systems

被引：1

作者：

Liu J.-L. ^{[1
]}

Dong X.-M. ^{[1
]}

Xue J.-P. ^{[1
]}

Wang H.-T. ^{[2
]}

机构：

[1] School of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi'an, 710038, Shaanxi

[2] Air Force Harbin Flight Academy, Harbin, 150000, Heilongjiang

来源：

Dong, Xin-Min (dongxinmin@139.com) | 2017年 / South China University of Technology卷 / 34期

基金：

中国国家自然科学基金;

关键词：

Composite energy function; Initial state error; Iterative learning control; Spatial motion systems; System uncertainties;

D O I：

10.7641/CTA.2017.60188

中图分类号：

学科分类号：

摘要：

In this paper, the tracking control problem for a class of uncertain motion systems which are iteratively running in the spatial domain is discussed. By introducing a spatial state differentiator operator and spatial composite energy function, a spatial period adaptive iterative learning control algorithm is proposed. First, the spatial state differentiator is utilized to transform the motion systems from the time formulation to the spatial formulation. Then, the controller is designed based on the spatial composite energy function. The system uncertainties are learned by the adapting law with projection operator, and an additional robust item is introduced to work concurrently with the learning mechanism to tackle the non-parametric uncertainties. With rigorous mathematical analysis, the convergence properties of tracking error are derived under the identical initial condition and random initial condition within a bound. Finally, a numerical example of a train tracking control is further provided to illustrate the effectiveness of the proposed algorithm. ©2017, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.

引用

页码：197 / 204

页数：7

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