Neuro-adaptive backstepping integral sliding mode control design for nonlinear wind energy conversion system

The electrical power extracted from a wind energy conversion system (WECS) tends to be inconsistent due to the intermittent nature of the wind. This issue is addressed by formulating a maximum power point tracking (MPPT) control strategy that optimizes the power extraction from the WECS under a wide range of wind speed profiles. This research article focuses on the formulation of a nonlinear neuro-adaptive backstepping integral sliding mode control (NABISMC) based MPPT strategy for a standalone, variable speed, fixed-pitch WECS equipped with a permanent magnet synchronous generator (PMSG). The proposed paradigm is a hybrid of the conventional backstepping and the integral sliding mode control (ISMC) based MPPT schemes. The effectiveness of the control strategy devised is guaranteed through numerical simulations carried out in Matlab/Simulink for a 3 kW PMSG-WECS under a stochastic wind speed profile. Further validation is guaranteed by giving a detailed performance comparison analysis of the proposed MPPT control strategy with the conventional feedback linearization control (FBLC), proportional integral derivative (PID) control, sliding mode control (SMC), and standard neuro-adaptive integral sliding mode control (NAISMC) based MPPT strategies, where the proposed strategy is found superior to all the stated strategies in terms of offering more accurate MPPT, lower steady state error, faster dynamic response and lesser chattering.