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On fault detection and isolation applied on unicycle mobile robot sensors and actuators

Abstract : In this paper, a combination of model-based and hardware redundancy methods is proposed for both sensor and actuator fault detection and isolation (FDI) of unicycle mobile robots. A focus is brought on robot drift-like faults on wheels and sensors. The goal is to detect and isolate the faulty component as early as possible. The proposed method is based on a combination of hardware redundancy and a bank of Extended Kalman Filters (EKF). Each filter is tuned for a specific fault, to generate residuals with different signatures under different component faults. The different signatures allow the fault isolation. Simulation results show that the proposed method allow to detect both wheels and sensors small drift-like faults and isolate them as early as possible. Fault Detection and Isolation (FDI), Unicycle mobile robot, Drift-like faults, Extended Kalman Filter (EKF), Hardware redundancy.
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Contributor : Samia Mellah <>
Submitted on : Friday, February 1, 2019 - 11:40:17 AM
Last modification on : Wednesday, January 20, 2021 - 3:12:27 AM
Long-term archiving on: : Thursday, May 2, 2019 - 3:58:29 PM


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  • HAL Id : hal-02003348, version 1



Samia Mellah, Guillaume Graton, El Mostafa El Adel, Mustapha Ouladsine, Alain Planchais. On fault detection and isolation applied on unicycle mobile robot sensors and actuators. 2018 7th International conference on Systems and Control (ICSC), Oct 2018, Valencia, Spain. pp.148-153. ⟨hal-02003348⟩



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