Abstract
The fast-growing technology of large scale wind turbines demands control systems capable of enhancing both the efficiency of capturing wind power, and the useful life of the turbines themselves. λ1-Optimal control is an approach to deal with persistent exogenous disturbances which have bounded magnitude (λ∞-norm) such as realistic wind disturbances and turbulence profiles. In this brief, we develop an efficient method to compute the λ1-norm of a system. As the control synthesis problem is nonconvex, we use the proposed method to design the optimal output feedback controllers for a linear model of a wind turbine at different operating points using genetic algorithm optimization. The locally optimized controllers are interpolated using a gain-scheduled technique with guaranteed stability. The controller is tested with comprehensive simulation studies on a 5 MW wind turbine using fatigue, aerodynamics, structures, and turbulence (FAST) software. The proposed controller is compared with a well-tuned proportional-integral (PI) controller. The results show improved power quality, and decrease in the fluctuations of generator torque and rotor speed.
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Jafarnejadsani, H., & Pieper, J. (2015). Gain-scheduled λ1-optimal control of variable-speed-variable-pitch wind turbines. IEEE Transactions on Control Systems Technology, 23(1), 372–379. https://doi.org/10.1109/TCST.2014.2320675
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