Adaptive quantized control for uncertain nonlinear systems with unknown control directions

被引：6

作者：

Wu, Jing ^{[1
]}

Sun, Wei ^{[1
]}

Su, Shun-Feng ^{[2
]}

Wu, Yuqiang ^{[3
]}

机构：

[1] Liaocheng Univ, Sch Math Sci, Liaocheng 252000, Shandong, Peoples R China

[2] Natl Taiwan Univ Sci & Technol, Dept Elect Engn, Taipei, Taiwan

[3] Qufu Normal Univ, Inst Automat, Qufu, Shandong, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL | 2021年 / 31卷 / 17期

基金：

中国国家自然科学基金;

关键词：

adaptive tracking control; hysteresis quantizer; Nussbaum function; unknown control directions; OUTPUT-FEEDBACK; NEURAL-CONTROL; INPUT; UNIFORM; MIMO;

D O I：

10.1002/rnc.5748

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 study reports adaptive quantized control for a class of uncertain strict-feedback nonlinear systems with unknown control directions. Combining backstepping technique and Lyapunov stability theory, a systematic analysis method is designed. Based on the disintegration of the hysteresis quantizer, a Nussbaum-based scheme can be developed to get over the obstacle of the quantized input signal and unknown control directions. Moreover, the number of adaptive laws is small, thereby reducing the computational burden. Then we testify the boundedness of all signals in the closed-loop system. Besides, the tracking error can converge to an arbitrarily small domain of origin. Finally, a simulation example is provided to verify the feasibility of the control scheme.

引用

页码：8658 / 8671

页数：14

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