Linear models‐based LPV modelling and control for wind turbines

Abstract

The non-linear behaviour of wind turbines demands control strategies that guarantee the robustness of the closedloop system. Linear parameter-varying (LPV) controllers adapt their dynamics to the system operating points, and the robustness of the closed loop is guaranteed in the controller design process. An LPV collective pitch controller has been developed within this work to regulate the generator speed in the above rated power production control zone. The performance of this LPV controller has been compared with two baseline control strategies previously designed, on the basis of classical gain scheduling methods and linear time-invariant robust H ∞ controllers. The synthesis of the LPV controller is based on the solution of a linear matrix inequalities system, proposed in a mixed-sensitivity control scenario where not only weight functions are used but also an LPV model of the wind turbine is necessary. As a contribution, the LPV model used is derived from a family of linear models extracted from the linearization process of the wind turbine non-linear model. The offshore wind turbine of 5 MW defined in the Upwind European project is the used reference non-linear model, and it has been modelled using the GH Bladed 4.0 software package. The designed LPV controller has been validated in GH Bladed, and an exhaustive analysis has been carried out to calculate fatigue load reductions on wind turbine components, as well as to analyse the load mitigation in some extreme cases.

Load reduction on a clipper liberty wind turbine with linear parameter‐varying individual blade pitch control

“…To avoid this additional measurement for the present design, the scheduling approach described in Lescher et al . and de Corcuera et al . is used.…”

Adaptive tower damping control for offshore wind turbines

“…LPV controllers have also been used for loads reduction, where the majority of the work considers above-rated wind conditions. [23][24][25] In an attempt to improve on the standard industrial approach to designing wind turbine controllers where each control loop is designed individually, a very enthusiastic approach is proposed in a study 17 that considers multiple-input multiple-output LPV control design with multiple performance objectives, namely RS control, drivetrain damping and tower fore-aft damping. The LPV controller covers both below-rated and above-rated wind conditions and is scheduled on the (estimated) wind speed.…”

Adaptive H<inf>∞</inf> control of large wind turbines

“…One of the approaches to achieve these goals is to improve the wind turbine control system. There has been a lot of research activity in this area and here are some of the relevant methods, along with the referenced application to wind turbines: Maximum Power Point Tracking (MPPT) [1], Individual Pitch Control (IPC) [2], H ∞ control [3], Linear Parameter-Varying (LPV) theory [4], [5], Model Predictive Control (MPC) [6], Quantitative Feedback Theory (QFT) [7], fuzzy control [8] etc. Application of these advanced control methods to wind turbines has two main goals: (i) increase in energy conversion efficiency, (ii) reduction of wind turbine structural loads.…”

“…LPV control can be regarded as an extension of H ∞ control theory to nonlinear and parameter-varying systems [9], [10]. In [4] and [5] LPV controllers are designed with the aim to ensure stability and performance guarantees in certain wind turbine operating regions. However, obtained controllers are not self-sufficient and they require additonal control loops (not encompassed by the LPV synthesis) in order to accomplish all control objectives.…”