We present two intelligent controllers for large and flexible wind turbines operating in high-speed winds, a Fuzzy-P + I and an adaptive neuro-fuzzy controller. The control objective is to regulate the rotor speed at the given rated power in region 3 (full load) via collective blade pitch angle. The modeled turbine is a three-bladed, upwind machine with a flexible blade and tower. We use the particle swarm optimization method in off-line training for our adaptive neuro-fuzzy controller. Numerical simulations are performed using wind inflow step change with a set of input–output data of a nonlinear wind turbine model. We compare the performance of the proposed controllers with the baseline PI-controller. Simulation results confirm successful performance of the proposed controllers.

Issue Section:
Research Papers
Keywords:
adaptive control, fuzzy control, intelligent control, neurocontrollers, numerical analysis, particle swarm optimisation, PI control, power generation control, rotors, wind turbines, fuzzy control, fuzzy-P+I, feuro-fuzzy, Wind turbine, particle swarm optimization
Topics:
Control equipment, Particle swarm optimization, Rotors, Wind turbines, Design, Blades, Wind

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