Robust and fault-tolerant linear parameter-varying control of wind turbines

Abstract

a b s t r a c tHigh performance and reliability are required for wind turbines to be competitive within the energy market. To capture their nonlinear behavior, wind turbines are often modeled using parameter-varying models. In this paper we design and compare multiple linear parameter-varying (LPV) controllers, designed using a proposed method that allows the inclusion of both faults and uncertainties in the LPV controller design. We specifically consider a 4.8 MW, variable-speed, variable-pitch wind turbine model with a fault in the pitch system.We propose the design of a nominal controller (NC), handling the parameter variations along the nominal operating trajectory caused by nonlinear aerodynamics. To accommodate the fault in the pitch system, an active fault-tolerant controller (AFTC) and a passive fault-tolerant controller (PFTC) are designed. In addition to the nominal LPV controller, we also propose a robust controller (RC). This controller is able to take into account model uncertainties in the aerodynamic model.The controllers are based on output feedback and are scheduled on an estimated wind speed to manage the parameter-varying nature of the model. Furthermore, the AFTC relies on information from a fault diagnosis system.The optimization problems involved in designing the PFTC and RC are based on solving bilinear matrix inequalities (BMIs) instead of linear matrix inequalities (LMIs) due to unmeasured parameter variations. Consequently, they are more difficult to solve. The paper presents a procedure, where the BMIs are rewritten into two necessary LMI conditions, which are solved using a two-step procedure.Simulation results show the performance of the LPV controllers to be superior to that of a reference controller designed based on classical principles.

H∞ Fault Tolerant Control of WECS Based on the PWA Model

“…Combining with Equation (17), model (16) can be translated into the following form: an effective wind estimator [16], where the realization method is described in [17][18][19][20]. The parameters are shown in Tables 1 and 2.…”

MixedH2/H∞pitch control of wind turbine with a Markovian jump model

“…Moreover, the stochastic characteristic of wind speed causes the the frequent switchings of wind turbine operating points, which brings further difficulty for control design to satisfy the above mentioned control strategy. Many authors have widely applied the modern control theory in the design of wind turbine control, such as linear-parameter-varying (LPV) control, model predictive control (MPC) or nonlinear feedback control, see [7,8,9,10,11,12,13,18,19,33,21,22,23,28,29,30,33]. Especially, [7] and [8] have designed the control law for wind turbine based on the gain scheduling method, where the switching law is satisfying a specific condition.…”

Fault Tolerant and Optimal Control of Wind Turbines with Distributed High-Speed Generators

“…In recent years, some model-based FTC approaches are proposed for wind turbines with conventional single generator drive trains: in [4], passive and active fault-tolerant controllers are designed and considered with regard to accommodating altered actuator dynamics in the pitch system model. In [5], a bank of unknown-input observers is used for fault diagnosis in the rotor and generator speed sensors of the fault detection isolation (FDI) benchmark model presented in [6].…”