Observer-based tracking control for MIMO pure-feedback nonlinear systems with time-delay and input quantisation

被引:21
|
作者
Liu, Wenhui [1 ]
Lim, Cheng-Chew [2 ]
Shi, Peng [2 ]
Xu, Shengyuan [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing, Jiangsu, Peoples R China
[2] Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA, Australia
基金
澳大利亚研究理事会;
关键词
Adaptive backstepping control; pure-feedback nonlinear systems; multiple-input and multiple-output (MIMO); neural networks; input quantisation; DYNAMIC SURFACE CONTROL; NEURAL-NETWORKS; CONTROL SCHEME; STABILIZATION;
D O I
10.1080/00207179.2016.1250162
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 addressing the adaptive neural backstepping control for multiple-input and multiple-output nonlinear systems in pure-feedback form with time-delay and input quantisation, we construct a high-gain state observer and an output-feedback adaptive control scheme using backstepping method, with neural networks to estimate the uncertain nonlinear functions. Then, we propose an output feedback neural controller that ensures all the state trajectories in the time-delay quantised nonlinear systems are ultimately bounded, with the control signal being quantised by either a hysteretic quantiser or a logarithmic quantiser. An illustrative example is presented to show the applicability of the new control method developed.
引用
收藏
页码:2433 / 2448
页数:16
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