Comments on Decentralized iterative learning control for a class of large scale interconnected dynamical systems by Hansheng Wu [J. Math. Anal. Appl. 327 (2007) 233-245]

JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS

卷:403

Editorial Material

Li, Xuefang¹  Xu, Jian-Xin¹  Yang, Shiping¹  Huang, Deqing¹ 

[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore

关键词: Large scale system;    Decentralized control;    Iterative learning control;    Asymptotic convergence;   

DOI  :  10.1016/j.jmaa.2013.02.027

来源: Elsevier

【 摘 要 】

In the reference paper Wu (2007) [1], a decentralized iterative learning control (ILC) algorithm is proposed aiming at achieving the asymptotic convergence of output errors for a class of linear time-varying large scale interconnected dynamic systems. The key points in the analysis of this decentralized ILC are the adoption of a specific time-weighted norm, and the use of a property of nondecreasing real functions that leads to the cancellation of interactions between subsystems. Here, on the one hand, we show that there exists a derivation problem in the proof, thus the asymptotic convergence property cannot be obtained. On the other hand, we provide an alternative analysis method, the classical contraction-mapping based 1LC analysis with the lambda-norm, to demonstrate that the decentralized ILC algorithm is still valid and able to achieve the asymptotic convergence. (C) 2013 Elsevier Inc. All rights reserved.

【 授权许可】

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