Non-fragile recursive sliding mode dynamic surface control with adaptive neural network

被引：4
作者：
机构：
[1] College of Aeronautics and Astronautics Engineering, Air Force Engineering University
[2] Unit 94270 of PLA
来源：
Liu, X. (liuxiafeu@126.com) | 1600年 / South China University of Technology卷 / 30期
关键词：
Dynamic surface control (DSC); Neural network; Non-fragile; Sliding mode control;
D O I：
10.7641/CTA.2013.30043
中图分类号：
学科分类号：
摘要：
A non-fragile recursive sliding mode dynamic surface adaptive control method is proposed for a class of uncertain, mismatched nonlinear system. By employing the neural network (NN) to approximate the system uncertainty and designing the recursive sliding mode dynamic surface to synthesize the interaction of the tracking error in each step of backstepping scheme, we make the method to get rid of the 'explosion of complexity' associated with the backstepping control and to avoid being fragile to the perturbation in both the filter time constant and adaptive parameters of neural network in the traditional dynamic surface control. Stability analysis verifies the semi-global, uniform, and ultimate boundedness (SUUB) for all the states of the closed-loop system, and guarantees the tracking error to converge to an arbitrarily small neighborhood of the origin.
引用
收藏
页码：1323 / 1328
页数：5
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