A modified control scheme based on the combination of online trained neural network and sliding mode techniques is proposed to enhance maximum power extraction for a grid connected permanent magnet synchronous generator (PMSG) wind turbine system. The proposed control method does not need the knowledge of the uncertainty bounds nor the exact model of the nonlinear system. Since the neural network is trained online, the time to estimate good weights can affect the dynamic performance of the process during the startup phase. Therefore an appropriate way to smoothly and explicitly accelerate the neural network rate of convergence during the startup phase is proposed. Furthermore, a flexible grid side voltage source converter control structure which can handle both grid connected and standalone modes based on conventional proportional integral (PI) control method is presented. Simulations are done in Matlab/Simulink environment to verify the effectiveness and assess the performance of the proposed controller. The results analysis shows the superiority of the proposed RBF neuro-sliding mode controller compared to a nonlinear controller based on sliding mode control method when the system undergoes parameter uncertainties.
This paper presents a simple and robust control strategy for a variable speed wind turbine conversion system using a squirrel-cage induction generator and a three-phase voltage source (AC/DC/AC) Pulse Width Modulation (PWM) converter connected to the utility grid through an LCL filter. The control strategy integrates for the generator side an adaptive radial basis function (RBF) neurosliding mode controller associated with the rotor flux oriented vector control which is used to regulate the turbine rotation speed, rotor flux, and the DC bus voltage. For the grid side, the inverter current and voltage regulation as well as the current injected into the grid are regulated by PI controllers for two modes of operation, namely, the stand-alone mode and grid connected mode. The main contribution of this article is the introduction of a new and simple control algorithm allowing automatic mode switching method based on wind speed. The proposed scheme is very efficient and can be easily implemented in practice. Simulation results illustrate the effectiveness and feasibility of the proposed algorithm.
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