Session: CIE-01-02 AMS General

Paper Number: 115133

115133 - A µ-Synthesis Approach for Robust Control of Wind Turbines 

Over the past few decades, the wind energy sector has witnessed a sustained growth in the physical size and power-rating
of wind turbines (WTs). Consequently, there has been increased weight and flexibility of WT components, which has exacerbated structural loading. Spatio-temporal variation of the wind field acts as a disturbance to a WT, causing nonlinearities. Advanced control methods have been proposed to mitigate fatigue loads in WTs. The linear models used for control design are based on assumptions which introduce errors during WT operation. Robust controllers address system nonlinearities and modeling errors. However, most rely on nominal models with no uncertainty description resulting in conservative robustness. In this contribution, a 𝜇-synthesis approach for designing a robust disturbance accommodating controller (RDAC) is proposed. A 5 MW reference WT (RWT) is used to evaluate of the proposed controller. A family of plants extracted from the RWT, allows generation of an uncertainty description for controller design. Its performance is compared with a gain-scheduled proportional-integral (GSPI) controller and an RDAC controller designed using nonsmooth H∞ synthesis. Simulation results show that the proposed controller improves tower load mitigation and speed regulation, without violating the turbine’s pitch-rate constraint or inducing additional loading in the rotor blades.
 

Presenting Author: Fateme Bakhshande Chair of Dynamics and Control, University of Duisburg-Essen, Duisburg, Germany

Presenting Author Biography: FATEME BAKHSHANDE (Member, IEEE) received his Ph.D. degree (Dr.-Ing.) in mechanical engineering from the University of Duisburg-Essen, Germany in 2018 and master's degree in control engineering from K. N. Toosi University of Technology, Tehran, Iran in 2011. She a is a Postdoctoral Fellow at the Chair of Dynamics and Control, University of Duisburg-Essen, Germany, since 2018. Her current research interests include model predictive control, robust and nonlinear control/observer, and vision-based control.

Authors:

Edwin Kipchirchir Chair of Dynamics and Control, University of Duisburg-Essen, Duisburg, Germany
Fateme Bakhshande Chair of Dynamics and Control, University of Duisburg-Essen, Duisburg, Germany
Dirk Söffker Chair of Dynamics and Control, University of Duisburg-Essen, Duisburg, Germany