Adaptive State Feedback—Theory and Application for Wind Turbine Control

Abstract

A class of adaptive disturbance tracking controllers (ADTCs) is augmented with disturbance and state estimation and adaptive state feedback, in which a controller and estimator, which are designed on the basis of a lower-order model, are used to control a higher-order nonlinear plant. The ADTC requires that the plant be almost strict positive real (ASPR) to ensure stability. In this paper, we show that the ASPR property of a plant is retained with the addition of disturbance and state estimation and state feedback, thereby ensuring the stability of the augmented system. The proposed adaptive controller with augmentation is presented in the context of maximum power extraction from a wind turbine in a low-wind-speed operation region. A simulation and comparative study on the National Renewable Energy Laboratory's (NREL's) 5 MW nonlinear wind turbine model with an existing baseline Proportional-Integral-Derivative(PID) controller shows that the proposed controller is more effective than the existing baseline PID controller.Keywords: wind energy; adaptive control; wind turbine control; maximum power point tracking BackgroundElectrical energy generated from wind power is one of the major sources of renewable energy. The size of the wind turbine has to be large in order to reduce the cost of the energy; however, this increase in size comes with the cost of added weights in its structures [1]. For large wind turbines, the blade is one of the most important structures that needs to be considered for both fatigue life and weights. Using stiff materials to construct wind turbine blades increases the blade's life, but it also increases its weight significantly. This requires a larger foundation and tower to support the blades, which results in high installation costs and an increase in the cost of energy. On the other hand, using lightweight materials reduces the weight significantly, but the blade becomes highly flexible, which makes it prone to damage by different types of aerodynamic and structural loading. Stiffening the blade is not a viable option for a large wind turbine. However, advents in modern control theory have made it possible to reduce the blade loading significantly, thereby making a flexible blade design a viable option [2]. Besides blade loading, other structural loading, such as drivetrain and tower loading, also needs to be considered to increase the life span of the wind turbine, which directly affects the cost of energy. Maximizing the power captured while operating the wind turbine at a below-rated wind speed is another important aspect of a wind turbine control system [3]. Modern wind turbines are capable of operating at variable rotor speeds to accompany the maximum power point tracking algorithm.

Proposed particle swarm optimization technique for the wind turbine control system

“…Jing et al 22 employed the sliding mode control for the 1.5-MW WT to control the pitch angle and maximize the power output. Thapa Magar et al 23 designed an adaptive controller for maximum power extraction and compared it with the PID controller. Olondriz et al 24 implemented a feedback PI controller to decrease the mechanical fatigue load of a WT, and the controller is optimized by pole and zero optimizers.…”