Robust output feedback adaptive sliding mode control for a class of uncertain nonlinear systems using robust adaptive fuzzy observer

IF 1.9 4区 数学 Q1 MATHEMATICS
A. A. Kalat, V. Mokhtari
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引用次数: 1

Abstract

This article presents a new robust adaptive sliding mode controller for a class of uncertain nonlinear systems whereas only the system output is measurable. Firstly, a robust adaptive fuzzy observer is designed for the system in order to estimate its state variables. The robust asymptotic convergence of the proposed observer is proven by Lyapunov direct method. Then based on the observation states, a robust adaptive sliding mode controller is suggested such that the closed loop system to be asymptotically stable. Robust asymptotic stability of the overall system suggested by the controller is also confirmed based on Lyapunov theory. Simulation results illustrate practicality and effectiveness of the proposed technique for controlling uncertain nonlinear systems.
基于鲁棒自适应模糊观测器的不确定非线性系统鲁棒输出反馈自适应滑模控制
针对一类只有系统输出可测的不确定非线性系统,提出了一种新的鲁棒自适应滑模控制器。首先,设计了鲁棒自适应模糊观测器来估计系统的状态变量。用Lyapunov直接方法证明了该观测器的鲁棒渐近收敛性。在此基础上,提出了一种鲁棒自适应滑模控制器,使闭环系统渐近稳定。基于李雅普诺夫理论,验证了该控制器所提出的整个系统的鲁棒渐近稳定性。仿真结果验证了该方法对不确定非线性系统控制的实用性和有效性。
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来源期刊
CiteScore
3.50
自引率
16.70%
发文量
0
期刊介绍: The two-monthly Iranian Journal of Fuzzy Systems (IJFS) aims to provide an international forum for refereed original research works in the theory and applications of fuzzy sets and systems in the areas of foundations, pure mathematics, artificial intelligence, control, robotics, data analysis, data mining, decision making, finance and management, information systems, operations research, pattern recognition and image processing, soft computing and uncertainty modeling. Manuscripts submitted to the IJFS must be original unpublished work and should not be in consideration for publication elsewhere.
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