FX-RLS-Based Feedforward Control for LIDAR-Enabled Wind Turbine Load Mitigation

Abstract

An adaptive feedforward controller based on a filtered-x recursive least square (FX-RLS) algorithm and a non-adaptive feedforward controller based on a zero-phase-error tracking control (ZPETC) technique have been designed to augment a collective pitch proportional-integral (PI) feedback controller for wind turbine rotor speed regulation and component load reduction when the wind turbine is operating above rated wind speed. The inputs to the adaptive feedforward controller include measurements of the rotor speed error and the incoming wind speed, where wind speed would be provided by a commercial light detection and ranging (LIDAR) system. Simulation results are based on comparison with a PI feedback only controller. Simulations show that augmenting the baseline PI feedback control with ZPETC feedforward control improves the blade loads but worsens the tower loads. The FX-RLS feedforward algorithm gives better performance than both the baseline PI feedback and the ZPETC feedforward in both tower (fore-aft and side-to-side) and blade (flapwise and edgewise) bending moment mitigation. Even with realistic 1 Hz LIDAR data update rate, the FX-RLS feedforward strategy can effectively mitigate the tower and blade bending moment while providing better rotor speed tracking and only a small energy drop.