Adaptive Neural-Fuzzy Sliding-Mode Fault-Tolerant Control for Uncertain Nonlinear Systems

被引：69

作者：

Wen, Shiping ^{[1
,2
,3
]}

Chen, Michael Z. Q. ^{[4
]}

Zeng, Zhigang ^{[1
,3
]}

Huang, Tingwen ^{[5
]}

Li, Chaojie ^{[6
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China

[2] Hamad bin Khalifa Univ, Coll Sci Engn & Technol, Doha 23874, Qatar

[3] Educ Minist China, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Hubei, Peoples R China

[4] Univ Hong Kong, Dept Mech Engn, Hong Kong, Hong Kong, Peoples R China

[5] Texas A&M Univ Qatar, Doha 23874, Qatar

[6] RMIT Univ, Platform Technol Res Inst, Melbourne, Vic 3001, Australia

来源：

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2017年 / 47卷 / 08期

关键词：

Actuator fault; actuator saturation; neural-fuzzy approximator; sliding-mode control (SMC); uncertain nonlinear system; GLOBAL EXPONENTIAL SYNCHRONIZATION; TRACKING CONTROL; INPUT SATURATION; TIME-DELAY; NETWORKS; CONSENSUS; SUBJECT; DESIGN;

D O I：

10.1109/TSMC.2017.2648826

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 proposes an adaptive neural-fuzzy sliding-mode control method for uncertain nonlinear systems with actuator effectiveness faults and input saturation. The parameter dependence of the control scheme is removed from the bound of actuator faults by updating online. A neural-fuzzy model is developed to approximate the uncertain nonlinear terms and a sliding-mode online-updating controller is developed to estimate the bound of the actuator with no prior knowledge of the fault. The asymptotic stability is verified via the Lyapunov method in the presence of actuator faults and saturation. Furthermore, the adaptive neural-fuzzy control method is extended to the uncertain faulty nonlinear systems with integral sliding-mode manifold as well as other popular sliding-mode surfaces. A numerical example is presented to demonstrate the effectiveness of the derived results.

引用

页码：2268 / 2278

页数：11

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