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Fault-Tolerant Model Predictive Control Trajectory Tracking for a Quadcopter with 4 Faulty Actuators

Abstract : In this paper, an active fault tolerant control (AFTC) framework is presented, with the ability to automatically estimate and compensate for the Loss Of Effectiveness (LOE) of all actuators of a quadcopter Unmanned Air Vehicle (UAV), while achieving trajectory tracking. The aforementioned AFTC framework consists of a reconfigurable controller based on Nonlinear Model Predictive Control (NMPC), and a fault detection and diagnosis (FDD) module based on a simple and computationally cheap nonlinear algebraic observer algorithm. The presented FDD module estimates the multiplicative faults in all quadcopter actuators simultaneously in an accurate and timely manner. A nonlinear simulation validates the proposed framework and proves a precise trajectory tracking performance in the presence of 4 simultaneous actuator faults. Furthermore, simulation results show that this framework is numerically tractable and real-time applicable, as the ratio of run-time to simulation time is much less than one.
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https://hal.archives-ouvertes.fr/hal-03478234
Contributor : Frédéric Davesne Connect in order to contact the contributor
Submitted on : Monday, December 13, 2021 - 8:12:39 PM
Last modification on : Wednesday, December 15, 2021 - 3:51:11 AM

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Akram Eltrabyly, Dalil Ichalal, Saïd Mammar. Fault-Tolerant Model Predictive Control Trajectory Tracking for a Quadcopter with 4 Faulty Actuators. 4th IFAC Conference on Embedded Systems, Computational Intelligence and Telematics in Control (CESCIT 2021), Jul 2021, Valenciennes, France. pp.141--146, ⟨10.1016/j.ifacol.2021.10.024⟩. ⟨hal-03478234⟩

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