Adaptive Fuzzy Control for Stochastic High-Order Nonlinear Systems With Output Constraints

被引：43
|
作者：
Fang, Liandi [1 ,2 ]
Ding, Shihong [1 ,3 ]
Park, Ju H. [4 ]
Ma, Li [1 ]
机构：
[1] Jiangsu Univ, Sch Elect & Informat Engn, Zhenjiang 212013, Jiangsu, Peoples R China
[2] Tongling Univ, Coll Math & Comp Sci, Tongling 244000, Peoples R China
[3] High Tech Key Lab Agr Equipment & Intelligence Ji, Zhenjiang 212013, Jiangsu, Peoples R China
[4] Yeungnam Univ, Dept Elect Engn, Kyongsan 38541, South Korea
来源：
IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2021年 / 29卷 / 09期
基金：
美国国家科学基金会; 新加坡国家研究基金会;
关键词：
Adaptive fuzzy control; adding a power integrator; barrier Lyapunov function (BLF); output constraints; stochastic nonlinear systems; FINITE-TIME STABILIZATION; TRACKING CONTROL;
D O I：
10.1109/TFUZZ.2020.3005350
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This article investigates the adaptive fuzzy control design for p-norm stochastic high-order lower triangular nonlinear systems with output constraints and unknown nonlinearities. First of all, a tan-type barrier Lyapunov function (BLF) is constructed to deal with the output constraint issue. Subsequently, an adaptive fuzzy control algorithm is developed by combining the constructed BLF with adding a power integrator technique. Simultaneously, the Lyapunov analysis shows that the designed controller can guarantee the boundness of all the variables in the closed-loop system in probability without violating the given output constraint. Finally, some comparative simulation results are provided to demonstrate the effectiveness of the proposed method.
引用
收藏
页码：2635 / 2646
页数：12
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