Adaptive neuro-fuzzy backstepping dynamic surface control for uncertain fractional-order nonlinear systems

被引：33
|
作者：
Song, Shuai [1 ]
Zhang, Baoyong [1 ]
Song, Xiaona [2 ]
Zhang, Zhengqiang [3 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Jiangsu, Peoples R China
[2] Henan Univ Sci & Technol, Sch Informat Engn, Luoyang 467023, Peoples R China
[3] Qufu Normal Univ, Sch Elect Engn & Automat, Rizhao 276826, Peoples R China
来源：
NEUROCOMPUTING | 2019年 / 360卷
基金：
中国国家自然科学基金;
关键词：
Backstepping control; Dynamic surface control; Fractional-order nonlinear systems; Neuro-fuzzy network system; SLIDING MODE CONTROL; TRACKING CONTROL; TIME-DELAY;
D O I：
10.1016/j.neucom.2019.06.014
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a fractional-order back stepping dynamic surface control (DSC) method is developed to cope with the stabilization problem for fractional-order nonlinear systems with uncertainties and external disturbances. In each step, a neuro-fuzzy network system is employed to approximate the unknown nonlinear function existing in fractional-order subsystem. Furthermore, a modified fractional-order filter is designed to avoid the problem of explosion of complexity caused by the recursive procedure. Then based on the fractional-order Lyapunov stability theory, the corresponding adaptive back stepping DSC controller is proposed to guarantee the stability of the fractional-order closed-loop systems. Finally, three examples are given in simulation part to demonstrate the validity of the proposed control method. (C) 2019 Published by Elsevier B.V.
引用
收藏
页码：172 / 184
页数：13
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