No abstract

Over the last few years, improving power extraction from the wind energy conversion system (WECS) under varying wind speeds has become a complex task. The current study presents the optimum maximum power point tracking (MPPT) control approach integrated with neural network (NN)-based rotor speed control and pitch angle control to extract the maximum power from the WECS. So, this study presents a reference model adaptive control (RMAC) for a direct-drive (DD) permanent magnet vernier generator (PMVG)-based WECS under real wind speed conditions. Initially, the RMAC-based rotor speed tracking control is presented with adaptive terms, which tracks a reference model that guarantees the expected exponential decay of rotor speed error trajectory. Then, to reduce the wind speed measurement errors, a recurrent neural network (RNN)-based training model is presented. Moreover, the asymptotic stability of the proposed control method is mathematically proven by Lyapunov theory. In addition, the pitch angle control is presented to efficiently operate the rotor speed within the allowable operating range. Eventually, the proposed control system demonstrates its effectiveness through simulation and experimentation using a prototype of 5 kW DD PMVG-based WECS. After that, the comparative results affirm the superiority of the proposed control method over existing control methods.

This study presents the coupling memory sampled-data control (CMSDC) design for the Takagi-Sugeno (T-S) fuzzy system that solves the stabilization issue of a surface-mounted permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS). A fuzzy CMSDC scheme that includes the sampled-data control (SDC) and memory sampled-data control (MSDC) is designed by employing a Bernoulli distribution order. Meanwhile, the membership function-dependent (MFD) H∞ performance index is presented, mitigating the continuous-time fuzzy system's disturbances. Then, by using Lyapunov-Krasovski functional with MFD $H_\infty$ performance index, data of sampling pattern and a constant signal transmission delay, sufficient conditions are derived. These sufficient conditions are linear matrix inequalities (LMIs), ensuring the global asymptotic stability of PMSG-based WECS under the designed control technique. Besides, the proposed method is demonstrated by a numerical simulation implemented on the PMSG-based WECS. Finally, Rossler's system demonstrates the effectiveness and superiority of the proposed method.