Application of Fuzzy Neural Network Sliding Mode Controller for Wind Driven Induction Generator System

An induction generator (IG) speed drive with the application of a sliding mode controller and a proposed fuzzy neural network (FNN) controller is introduced in this paper. Grid connected wind energy conversion system (WECS) present interesting control demands, due to the intrinsic nonlinear characteristic of wind mills and electric generators. The FNN torque compensation is feedforward to increase the robustness of the wind driven induction generator system. A multivariable controller is designed to drive the turbine speed to extract maximum power from the wind and adjust to the power regulation. Moreover, a sliding mode speed controller is designed based on an integral-proportional (IP) sliding surface. When sliding mode occurs on the sliding surface, the control system acts as a robust state feedback system.

I. INTRODUCTION

WIND Energy is an inexhaustible, sanitary and renewable resource. Many governments are attracted by the WECS with its simple structure, easy maintenance and management. On account of the development and the wide application of power electronics, the technologies of generating electricity by wind energy have proceeded quickly. It has becomes a vital renewable resource for environmental protection adopted worldwise.