Wind turbine control using T-S systems with nonlinear consequent parts

In this paper, a novel T-S model with nonlinear consequent parts is introduced for the variable speed, variable pitch wind turbine. Because there is an inherent uncertainty in wind speed measurement, a fuzzy observer is proposed to estimate the effective wind speed, acting on the turbine's blades. Then, a robust H∞ observer based fuzzy controller is designed to control the turbine using the estimated wind speed. Also, two artificial neural networks are used to accurately model the aerodynamic curves. In contrast to traditional controllers, which have different control schemes for different working regions, in this paper, only one controller is used for all operating regions of the wind turbine. As the main goal of a wind turbine is to maximize energy production and minimize mechanical loads concurrently, in addition to rotor dynamics, blade and tower dynamics are taken into account. To show the effectiveness of the proposed controller, simulations are performed on a 5 MW wind turbine simulator, in different wind profiles. Results show that compared with standard baseline controller, whilst power generation is improved, mechanical loads are reduced considerably. •T-S model with nonlinear consequent part is employed for both controller and observer design.•A robust fuzzy observer for wind speed estimation is introduced.•The separation principle of the proposed observer and controller is proved, despite that the premise variable of the T-S model is unmeasured.•In contrast to traditional controllers, which have different control schemes for different working regions, in this paper, only one controller is used for all operational regions of wind turbine.•Power generation maximization and mechanical load suppression are taking into account concurrently.