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research-article

Design of Repetitive-Control System with Input Dead Zone Based on Generalized Extended-State Observer

[+] Author and Article Information
Min Wu

Professor School of Automation China University of Geosciences Wuhan, Hubei 430074, ChinaHubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan, Hubei 430074, China
wumin@cug.edu.cn

Pan Yu

Student School of Information Science and Engineering Central South University Changsha, Hunan 410083, ChinaHubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan, Hubei 430074, China
1545906230@qq.com

Xin Chen

Professor School of Automation China University of Geosciences Wuhan, Hubei 430074, ChinaHubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan, Hubei 430074, China
chenxin@cug.edu.cn

Jinhua She

Professor School of Automation China University of Geosciences Wuhan, Hubei 430074, ChinaHubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan, Hubei 430074, ChinaSchool of Engineering Tokyo University of Technology Hachioji, Tokyo 192-0982, Japan
she@stf.teu.ac.jp

1Corresponding author.

ASME doi:10.1115/1.4035615 History: Received April 27, 2016; Revised December 22, 2016

Abstract

This paper concerns a repetitive-control system with an input-dead-zone (IDZ) nonlinearity. First, the expression for the IDZ is decomposed into a linear term and a disturbance-like one that depends on the parameters of the dead zone. A function of the system state error is use to approximate the combination of the disturbance-like term and an exogenous disturbance. The estimate is used to compensate for the overall effect of the IDZ and the exogenous disturbance. Next, the state-feedback gains are obtained from a linear matrix inequality that contains two tuning parameters for adjusting control performance; and the pole assignment method is employed to design the gain of a state observer. Then, two stability criteria are used to test the stability of the closed-loop system. The method is simple, employing neither an inverse model of the plant nor an adaptive control technique. It is also robust with regard to the different parameters of the IDZ, uncertainties in the plant, and the exogenous disturbance. Finally, two numerical examples demonstrate the effectiveness of this method and its advantages over others.

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