Memory-based ISMC design of DFIG-based wind turbine model via T-S fuzzy approach

Abstract

This paper investigates the memory-based integral sliding mode control (SMC) design for nonlinear doubly fed induction generator model. The proposed nonlinear doubly fed induction generator model is equivalent to linear sub-systems via fuzzy membership functions by utilising the Takagi–Sugeno fuzzy approach. Then, a memory-based sliding surface is intended, which is different from the conventional sliding surface. Based on suitable Lyapunov functionals and slack matrices, sufficient conditions are obtained, which guaranty the memory-based Takagi–Sugeno fuzzy system to be globally asymptotically stable under the designed memory-based sliding mode control through linear matrix inequality. Further, the desired memory-based fuzzy SMC control gain is obtained by solving the concerned linear matrix inequality. Also, a memory-based SMC law and an adaptive SMC law are incorporated to make the system state trajectories onto the pretend sliding switching manifold in a finite-time. The derived conditions are verified in the numerical section with the nonlinear doubly fed induction generator model, which are formulated for reflecting the characteristics of the proposed wind turbine model.