A Lyapunov Based Switching Control to Track Maximum Power Point of WECS.

Abu Jami’in, Mohammad and Hu, Jinglu and Julianto, Eko (2016) A Lyapunov Based Switching Control to Track Maximum Power Point of WECS. International Joint Conference on Neural Networks (IJCNN) (16). ISSN 978-1-5090-0620-5

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Abstract

The control system is a key technology to extract maximum energy from the incident wind. By regulating aerodynamic control, it is possible to adapt the changes in wind speed by controlling shaft speed. Thus, the turbine generator can track maximum power extracted from wind. In this paper, we propose a Lyapunov based switching control under quasi-linear ARX neural network (QARXNN) model to track maximum power of wind energy conversion system. The switching index is used to measure the stability of nonlinear controller and selects linear or nonlinear controller in order to ensure the stability. Interestingly, a simple switching law can be built utilizing the parameters of model directly. Finally, we have compared the proposed algorithm of switching controller with another algorithm. The results show that the proposed algorithm has better control performance.

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