Intelligent Sliding Mode Control Under Maximum Power Point Tracking with Indirect Speed Controller Strategy for Mechanical Wind Turbine System

Abstract

This paper introduces an advanced sliding mode control (SMC) approach integrated with a maximum power point tracking (MPPT) strategy, designed for two-mass variable speed wind turbine (VSWT) systems. The method employs an indirect speed controller (ISC) to set the reference electromagnetic torque based on the turbine's maximum power curve. However, the close coupling between electromagnetic torque (T_em) and rotational speed (Ω_m) in the ISC limits dynamic flexibility, leading to slower system responses due to mechanical coupling effects. To address this, the proposed ANN-SMC model leverages the robustness of SMC and the adaptability of artificial neural networks (ANN) to enhance decoupling between T_em and Ω_m. This ensures optimal performance even in uncertain conditions. The experiment will be conducted on three types of wind conditions: steady, turbulent, and gusty. Simulation results in Matlab/Simulink validate the model's effectiveness in meeting dynamic performance goals.