Linear Modeling of Doppler Wind Lidar Systems for Gust Load Alleviation Design

Abstract

Preview control using wind estimates derived from Doppler wind lidar measurements is a promising technique for designing active gust load alleviation functions. Due to the relatively high noise levels in the lidar measurements, the associated estimator must use some type of smoothing to obtain a usable estimate for gust load alleviation. In the resulting wind estimate, this results in the loss of some of the information as well as a filtered and reduced component of the measurement noise. Taking the losses and noise into account during control synthesis should help ease the tuning procedure and improve the performance and robustness of the resulting controller. This paper proposes a method based on a maximum a posteriori interpretation of the wind estimation problem to consistently produce linear filters that closely approximate the behavior of the complete measurement chain (sensor and wind estimator) and that can be integrated into a linear control synthesis framework. Its characteristics are shown to closely match those of the real estimator over a range of types of turbulence using a standard set of system parameters.