Optimal multivariable control for wind energy conversion systems using particle swarm optimization technique

摘要

This paper presents a robust multivariable control design for a variable-speed variable-pitch wind turbine (VSVPWT). This multivariable control approach is based on a combination of a linear proportional and integral (PI) control strategy for blade pitch angle and a nonlinear torque integral sliding mode control (ISMC) technique. Thus, the proposed controlling method is associated to general regression neural network (GRNN) to estimate the uncertain part of the system, and particle swarm optimization-based evolutionary algorithm to improve the controller performances by optimizing PI and ISMC gains. The stability of the multivariable control system was investigated by the Lyapunov theory. In addition, a comparison with other control strategies such as PI and SMC controllers is reported. We noticed from the simulation results that the proposed controller presents satisfactory performances in term of transition response and tracking error level.