Fault Tolerant Control for Wind Turbine System Based on Model Reference Adaptive Control and Particle Swarm Optimization Algorithm

This paper tackles the problem of Fault Tolerant Control (FTC) for Wind Turbine System. Motivated by the Model Reference Adaptive Control (MRAC) and the Particle Swarm Optimization Algorithm (PSOA), the main contribution of this work is to provide online tuning for the wind turbine controller. In order to achieve the required system performances, even during components and/or system faults, our proposed strategy takes care of an adaptive controller in which the desired performance is expressed in terms of a reference model. The controller parameter adjustments are made using the stability theory that involves the gradient function and the Lyapunov function. Moreover, the minimization of the fitness function of PSOA allows convergence of the proposed MRAC to an optimal point, owing to redistribution of the control signals when a failure or noise occurs. The simulation results have shown good performance than some existing approaches in the literature.