Fuzzy Neural Network PID Control for Direct Drive Wave Power Generation System

In this paper, based on the analysis of float hydrodynamic model and permanent magnet synchronous linear generator (PMSLG) model, the maximum power capture conditions are obtained. Then, an improved fuzzy neural network PID (IFNNP) control algorithm is applied to the maximum power point tracking control. Through the analysis of the structure of fuzzy neural network, IFNNP control is constructed by adding a designed activation function to the fuzzy neural network. Fuzzy rules are combined with the self-learning ability of neural network to adjust the PID parameters according to the changing sea conditions, so that IFNNP algorithm can approach the non-linear target model more accurately. The simulation results show that the wave energy converter system with the proposed strategy is effective and feasible.