Approximation-based adaptive fuzzy control for a class of non-strict-feedback stochastic nonlinear systems

被引：17
|
作者：
Wang HuanQing [1 ,2 ]
Chen Bing [2 ]
Lin Chong [2 ]
机构：
[1] Bohai Univ, Sch Math & Phys, Jinzhou 121000, Peoples R China
[2] Qingdao Univ, Inst Complex Sci, Qingdao 266071, Peoples R China
来源：
SCIENCE CHINA-INFORMATION SCIENCES | 2014年 / 57卷 / 03期
关键词：
stochastic nonlinear systems; in non-strict-feedback form; adaptive control; fuzzy control; backstepping approach; SMALL-GAIN APPROACH; TRACKING CONTROL; NEURAL-CONTROL; DECENTRALIZED STABILIZATION; ROBUST-CONTROL; DESIGN;
D O I：
10.1007/s11432-013-4785-x
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 paper considers the problem of adaptive fuzzy control of a class of single-input/single-output (SISO) nonlinear stochastic systems in non-strict-feedback form. Fuzzy logic systems are used to approximate the uncertain nonlinearities and backstepping technique is utilized to construct an adaptive fuzzy controller. The proposed controller guarantees that all the signals in the resulting closed-loop system are bounded in probability. The main contribution of this note lies in providing a control strategy for a class of nonlinear systems in non-strict-feedback form. Simulation result is used to test the effectiveness of the suggested approach.
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收藏
页码：1 / 16
页数：16
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