Sliding Mode Control Optimized by Teaching Learning-Based Optimization Algorithm for Variable Speed Wind Turbine System

摘要

The paper presents a design of sliding mode control with a modified surface, type Proportional Integral Derivative (PID), optimized by the teaching learning-based optimization algorithm (TLBO-PID-SMC) to control the speed wind turbine. The TLBO algorithm is applied in this paper to tune optimally of the three parameters (Kp, Ki, Kd) of the PID sliding surface. The principal objective of the proposed controller is to eliminate the chattering presented in the conventional sliding mode control and for enhancing the tracking error performance which guarantees a maximum wind power extraction. The developed sliding mode controller is applied in order to the actual trajectory follows the required trajectory in spite of presence of the uncertainties, and nonlinear dynamics. The Stability of the wind turbine system is mathematically proved by Lyapunov theorem. The developed method is compared with the PID-SMC and the conventional SMC, the results of simulations show the better tracking performance of the developed method (TLBO-PID-SMC) with less oscillations and quick settling time compared to other controller which demonstrates the validity and the stability of the developed method even with the uncertainties.