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Input‐output based fault estimation for linear systems with partially dynamic uncertainty and actuator faults
Author(s) -
Huang ShengJuan,
Yang GuangHong
Publication year - 2016
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3523
Subject(s) - control theory (sociology) , actuator , fault (geology) , convergence (economics) , trace (psycholinguistics) , stability theory , computer science , fault detection and isolation , exponential stability , mathematics , control (management) , nonlinear system , linguistics , philosophy , physics , quantum mechanics , artificial intelligence , seismology , economic growth , economics , geology
Summary This paper is concentrated on the problem of fault estimation for a class of linear systems with partially dynamic uncertainty and actuator faults. A novel input–output‐based fault estimation approach is proposed, by which the estimates can asymptotically converge to the magnitudes of the actuator faults, and the asymptotic convergence of the estimation is theoretically proved. Some important properties related to the corresponding fault errors are obtained. The proposed input–output‐based fault estimation method can exponentially weaken the effects of the fault derivatives on the fault error dynamics. Based on the online estimates, a corresponding robust fault‐tolerant control policy is designed, so that the closed‐loop system is asymptotically stable and the control output curves can asymptotically trace to the normal control output curves. Finally, three examples are given to show the effectiveness, merits, and applications of the proposed methods. Copyright © 2016 John Wiley & Sons, Ltd.