Adaptive quantized tracking control for a class of uncertain nonlinear systems with guaranteed transient performance

被引:9
|
作者
Jing, Yan-Hui [1 ]
Yang, Guang-Hong [1 ,2 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Liaoning, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2018年 / 355卷 / 13期
基金
中国国家自然科学基金;
关键词
MARKOVIAN JUMP SYSTEMS; INPUT QUANTIZATION; FEEDBACK STABILIZATION; LIMITED INFORMATION; CONTROL SCHEME; OUTPUT; CONSTRAINTS; SIGNAL;
D O I
10.1016/j.jfranklin.2018.06.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, an adaptive quantized control method with guaranteed transient performance is presented for a class of uncertain nonlinear systems. By introducing the Nussbaum function technique, the difficulty caused by quantization is handled and a novel adaptive control scheme is designed. In comparing with the existing adaptive control scheme, the key advantages of the proposed control scheme are that the controller needs no information about the parameters of the quantizer and the stability of the closed-loop system and the transient performance are independent of the coarseness of the quantizer. Based on Lyapunov stability theory and Barbalat's Lemma, it is proven that all the signals in the resulting closed-loop system are bounded and the tracking error converges to zero asymptotically with the prescribed performance bound at all times. Simulation results are presented to verify the effectiveness of the proposed control method. (C) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:5414 / 5430
页数:17
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