Dependable power extraction in wind turbines using model predictive fault tolerant control

Abstract

In this paper, a fault tolerant model predictive control scheme is proposed for wind turbines in the partial-load region to meet the control objectives in the presence of disturbances, uncertainties, sensor and actuator faults. The aim of wind turbine control systems in the partial-load region is to capture maximum power by tracking the optimal generator speed. But any fault in the sensors and actuators can take away the closed-loop system from the main objectives and maybe make the system unstable in some cases. At first, an online model predictive controller (MPC) is designed as a nominal controller to track the maximum power and guarantee all constraints satisfaction without considering any fault. In the next step, an adaptive sliding mode observer (SMO) is designed to estimate the actual states and sensor faults, simultaneously. Finally, an additive control law is represented and shown that it is able to tolerate the actuator faults effectively. Using extensive simulation results it is shown that the proposed strategy is able to handle the uncertainties, sensor and actuator faults in the control system, simultaneously.