Unknown input observers for fault diagnosis in Lipschitz nonlinear systems

Xiaoxu Liu, Zhiwei Gao

Research output: Contribution to conferencePaperpeer-review

11 Citations (Scopus)

Abstract

This paper considers the problem of robust fault detection for Lipschitz nonlinear systems impaired by faults and unknown inputs in both process and sensors. The purpose of the proposed strategy is to estimate both the system states and the considered faults existing in actuators as well as sensors while minimize the influences from disturbances. An innovative robust observer design methodology is developed through an integration of fault estimation approach and unknown input observer (UIO). In contrast to previous studies, the considered unknown inputs do not only exist in system process but also sensors. Moreover, to meet the practical engineering situations, they are not assumed to be decoupled completely. With the assist of linear matrix inequality (LMI) method, observer parameters are determined to attenuate the influences of unknown inputs which cannot be decoupled, as well as guarantee the stability of the estimation dynamics. Simulation results are presented to demonstrate that the proposed observer scheme performs reasonably well.
Original languageEnglish
Publication statusPublished - Aug 2015
EventInternational Conference on Mechatronics and Automation - Beijing
Duration: 1 Aug 2015 → …

Conference

ConferenceInternational Conference on Mechatronics and Automation
Period1/08/15 → …

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