Control for PMSG wind energy conversion system based on Adaptive Fuzzy Logic Controller

In this work, after behavior analysis of sliding mode controllers, we proposed an Adaptive fuzzy controller inspired by the sliding mode control. The controller uses two separate variables to estimate the surface and distance away from the setpoint. The progressive command is calculated based on a set of fuzzy rules that we developed. This surface is often a linear function of the successive regulation errors and the algebraic value of the parameter delta. This parameter is considered the first variable for surface estimation. The principle is to bring the current operating point by an adequate command towards this surface. To ensure the stability of the fault dynamics, the second part explains the principle of convergence from the operating point to the equilibrium point by using the distance variable. The AFLC controller with adaptive tuning is applied and capable of controlling complex non-linear systems in the presence of different perturbations. The simulation results under MATLAB / Simulink prove the improved performance of the proposed MPPT in terms of energy efficiency, reliability under different environmental conditions, and dynamic performance compared to conventional control.