Adjustable dimension descriptor observer based fault estimation of nonlinear system with unknown input

Jian Han, Xiuhua Liu, Xinjiang Wei, Huifeng Zhang and Xin Hu

Applied Mathematics and Computation, 2021, vol. 396, issue C

Abstract: In this paper, the fault estimation problem is considered for nonlinear system with process fault, sensor fault and unknown input. A novel adjustable dimension augmented descriptor observer is designed. Based on the proposed observer, the system state, process and sensor faults can be estimated simultaneously, and the unknown input can be decoupled from the error dynamic. The observer parameters are calculated by solving LMI and matrix equations. The observer order can be selected in a certain range, which is helpful to achieve the compromise between the estimation cost and accuracy. At last, two simulation examples are listed to show the effectiveness of the proposed approach.

Keywords: Fault estimation; Adjustable dimension; Disturbance decoupling; Disturbance attenuation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:396:y:2021:i:c:s0096300320308523

DOI: 10.1016/j.amc.2020.125899

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