Adaptive neural dynamic surface control for servo systems with unknown dead-zone

被引：127
|
作者：
Na, Jing [1 ,2 ]
Ren, Xuemei [2 ]
Herrmann, Guido [3 ]
Qiao, Zhi [2 ]
机构：
[1] Kunming Univ Sci & Technol, Fac Mech & Elect Engn, Kunming 650093, Peoples R China
[2] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
[3] Univ Bristol, Dept Mech Engn, Bristol BS8 1TR, Avon, England
来源：
CONTROL ENGINEERING PRACTICE | 2011年 / 19卷 / 11期
基金：
中国国家自然科学基金;
关键词：
Adaptive control; Dead zone; Dynamic surface control (DSC); Time-delay systems; Neural networks; TIME-DELAY SYSTEMS; UNCERTAIN NONLINEAR-SYSTEMS; PURE-FEEDBACK FORM; NETWORK CONTROL; TRACKING CONTROL; INPUT; IDENTIFICATION; DESIGN;
D O I：
10.1016/j.conengprac.2011.07.005
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An adaptive neural controller is proposed for nonlinear systems with a nonlinear dead-zone and multiple time-delays. The often used inverse model compensation approach is avoided by representing the dead-zone as a time-varying system. The "explosion of complexity" in the backstepping synthesis is eliminated in terms of the dynamic surface control (DSC) technique. A novel high-order neural network (HONN) with only a scalar weight parameter is developed to account for unknown nonlinearities. The control singularity and some restrictive requirements on the system are circumvented. Simulations and experiments for a turntable servo system with permanent-magnet synchronous motor (PMSM) are provided to verify the reliability and effectiveness. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1328 / 1343
页数：16
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