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Fault-tolerant control is essential in guaranteeing the stability and reliability of non-linear real-time systems such as Quadrotor UAVs. Controllers based on this approach are capable of estimating and compensating for faults, model uncertainties, and disturbances in a system. While passive fault-tolerant control is widely used, it is not capable of addressing faults that are not predefined in the control setup. In contrast, active fault-tolerant control can detect, estimate, and compensate for any faults in the system. In the recent past, researchers have enhanced this control approach using artificial neural networks and metaheuristic optimization algorithms. This paper uses a Proportional-Integral-Derivative (PID) controller based on Genetic Algorithms (GA) in conjunction with Active Disturbance Rejection Control (ADRC) to provide optimal control gains for the quadrotor and improve fault tolerance. The Quadrotor UAV system was modeled considering actuator loss-ofeffectiveness and sine wave disturbances. The system was simulated and analyzed in MATLAB to demonstrate the effectiveness of the proposed approach. Results showed good performance of the controller in handling faults and disturbances, ensuring stability, and continuously optimizing control gains in real time.
Siame et al. (Thu,) studied this question.