Fuzzy Adaptive Finite-Time Tracking Control for a Class of Nonlinear Systems: An Event-Triggered Quantized Control Scheme

被引:9
|
作者
Jiang, Yunbiao [1 ]
Liu, Zhongxin [1 ]
Chen, Zengqiang [1 ]
机构
[1] Nankai Univ, Sch Artificial Intelligence, Tianjin Key Lab Brain Sci & Intelligent Rehabil, Tianjin 300350, Peoples R China
基金
中国国家自然科学基金;
关键词
Filtered backstepping; finite-time control (FTC); full-state constraints; fuzzy logic systems; nonlinear systems; DYNAMIC SURFACE CONTROL; FULL-STATE CONSTRAINTS; FEEDBACK-SYSTEMS; STABILITY; SUBJECT; DESIGN;
D O I
10.1109/TFUZZ.2023.3273551
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This brief proposes a fuzzy adaptive event-triggered quantized finite-time control (FTC) (ETQFTC) scheme for uncertain strict-feedback nonlinear systems with full-state constraints. By means of state transformation, filtered backstepping technique and fuzzy adaptive control with the idea of minimum learning parameter, a C-1 ETQFTC scheme with low differential calculation and few parameter updates is developed. In the proposed scheme, the feasibility condition generally required in the existing state-constrained control, and the control chattering and singularity problem, which are common in the existing FTC schemes are removed and avoided respectively. Finally, complete stability analysis and a set of comparative simulations are presented.
引用
收藏
页码:4137 / 4144
页数:8
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