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Robust Fuzzy Observer-Based Fault Tolerant Tracking Control for Nonlinear Systems with Simultaneous Actuator and Sensor Faults: Application to a DC Series Motor Speed Drive

Katherin Indriawati(1*), Noboru Sebe(2), Trihastuti Agustinah(3), A. Jazidie(4)

(1) Engineering Physics Department, Institut Teknologi Sepuluh November Surabaya, Indonesia
(2) Department of Artificial Intelligence Kyushu Institute of Technology, Japan
(3) Department of Engineering Physics, Faculty of Industrial Technology, Sepuluh November Institute of Technology, Kampus ITS Keputih Sukolilo, Surabaya, Indonesia
(4) Department of Engineering Physics, Faculty of Industrial Technology, Sepuluh November Institute of Technology, Kampus ITS Keputih Sukolilo, Surabaya, Indonesia
(*) Corresponding author


DOI: https://doi.org/10.15866/ireaco.v8i6.7505

Abstract


In this paper, a detailed design scheme for observer-based robust fault estimation and fault tolerant tracking control (FTTC) is developed for a class of nonlinear system described by a T-S fuzzy model subjected to both sensor and actuator faults simultaneously. The proposed scheme includes a single robust fuzzy observer (using the extended state system formulation) and an observer-based FTTC (using compensation scheme) to guarantee given stability requirements, while limiting the influence of noises and disturbances. Sufficient conditions for the robust stability of the proposed fuzzy observer are formulated in terms of linear matrix inequalities (LMIs) that can be conveniently solved using LMI optimization techniques. Based on the idea of a corrective control law and a corrective measurement output, the estimation results of the proposed observer are used to provide the FTTC system without changing the existing nominal control law. Thus this approach can be applied to general nonlinear control system. Finally, the validity and applicability of the proposed approach are shown by a numerical example of a DC series motor speed drive system.
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Keywords


DC Series Motor Speed Drive; Fault Estimation; Reconfigurable Control; Robust Fuzzy Observer

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References


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