Adaptive Neural Network Finite-Time Output Feedback Control of Quantized Nonlinear Systems

被引：400
|
作者：
Wang, Fang [1 ,2 ]
Chen, Bing [2 ]
Lin, Chong [2 ]
Zhang, Jing [3 ]
Meng, Xinzhu [1 ]
机构：
[1] Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China
[2] Qingdao Univ, Inst Complex Sci, Qingdao 266071, Peoples R China
[3] Guangdong Univ Foreign Studies, Comp Sci & Technol, Guangzhou 510006, Guangdong, Peoples R China
来源：
IEEE TRANSACTIONS ON CYBERNETICS | 2018年 / 48卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Adaptive neural control; finite-time; output-eedback; quantized nonlinearsystems; COORDINATION CONTROL; UNCERTAIN SYSTEMS; STABILIZATION; DELAY; MODEL; DESIGN;
D O I：
10.1109/TCYB.2017.2715980
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 addresses the finite-time tracking issue for nonlinear quantized systems with unmeasurable states. Compared with the existing researches, the finite-time quantized feedback control is considered for the first time. By proposing a new finite-time stability criterion and designing a state observer, a novel adaptive neural output-feedback control strategy is raised by backstepping technique. Under the presented control scheme, the finite-time quantized feedback control problem is coped with without limiting assumption for nonlinear functions.
引用
收藏
页码：1839 / 1848
页数：10
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