Intelligent control of a DFIG wind turbine using a PSO evolutionary algorithm

This paper presents an intelligent proportional integral sliding mode controller (iPI-SMC) for power capture optimization of a doubly fed induction generator (DFIG) based wind turbine system. The designed method is based on a combination of proportional integral (PI) control, swarm optimization and sliding mode control (SMC). For this approach, the PI action is included in the sliding surface in order to improve the performances of standard SMC. Thus, the proposed controlling method is associated to particle swarm optimization (PSO) based evolutionary algorithm to improve the controller performances by optimizing PI and SMC gains. The stability of the system using the proposed controller is investigated by Lyapunov theory. The simulation results of the investigated PSO based PI-SMC method are compared with integral sliding mode control (ISMC) as well as conventional SMC. The results reveal that the proposed controller presents low tracking error and less chattering. In addition, the proposed method shows more robustness to uncertainties and faster transient response compared to the others methods control (i.e. ISMC and SMC).