Adaptive Control of Noncanonical Nonlinear Systems With Unknown Input Dead-Zone Characteristics

被引:0
|
作者
Lai, Guanyu [1 ,2 ]
Tao, Gang [2 ]
Zhang, Yun [1 ]
机构
[1] Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Guangdong, Peoples R China
[2] Univ Virginia, Dept Elect & Comp Engn, Charlottesville, VA 22903 USA
来源
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2018年
关键词
NEURAL-CONTROL;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Unlike traditional canonical nonlinear systems, the nonlinear system in noncanonical form does not have an explicit relative degree structure and cannot be transformed into a canonical form via a parameter-independent diffeomorphism. In this sense, controlling noncanonical nonlinear system is very difficult and challenging. To address this problem, in this paper, we study the adaptive control of noncanonical nonlinear systems with unknown input dead zone. A new Lyapunov-based control scheme and a new gradient control scheme are developed successively with the techniques of feedback linearization, adaptive dead-zone inverse compensation and system parametrization, to address the relative-degree-one and relative-degree-two cases of the considered noncanonical nonlinear system, respectively. The closed-loop stability and the asymptotic tracking are ensured with the proposed adaptive schemes, and the effectiveness of the obtained results will be illustrated through simulation studies.
引用
收藏
页码:5524 / 5529
页数:6
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