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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
基金:
新加坡国家研究基金会;
美国国家科学基金会;
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.
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页码:2635 / 2646
页数:12
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