Simplified adaptive neural network-based maximum wind energy capture control for wind generator system

This paper presents the maximum wind energy capture (MWEC) control for wind generator system with simplified neural network adaptive method. The design procedure in this paper aims at designing stable simplified neural network adaptive slide mode controllers, adopting simple 1-D network weight estimators, that guarantee the existence of the system poles in some predefined zone and exacting maximum wind energy capture. Moreover, with our control strategy, the maximum wind energy capture control problems are reduced to Lyapunov stability problem. In this way, by solving the stability Lyapunov functions, the feedback gains which guarantee global asymptotic stability and desired maximum wind energy capture performance are determined. The results are applied to wind generator systems, and numerical simulation showing the feasibility of the proposed method.