Fault Tolerant Control of Wind Turbine with Sensor and Actuator Faults

Abstract

This paper presents a fault-tolerant control technique for wind turbine systems with sensor and actuator faults. The control objective is to maximize power production and minimize turbine loads by calculating a desired pitch angle within their limits. Any fault with a sensor and actuator can cause significant error in the pitch position of the corresponding blade. This problem may result in insufficient torque such that the power reference cannot be achieved. In this paper, a fault-tolerant control technique using a robust dynamic inversion observer and control allocation is employed to achieve successful pitch control despite these faults in the sensor and actuator. The observer based detection method is used to detect and isolate sensor faults by checking whether errors are larger than threshold values. In addition, the control allocation technique is adopted to tolerate actuator fault. Control allocation is one of the most commonly used faulttolerant control techniques, especially for over-actuated systems. Further, the control allocation method can be used to achieve the power reference even in the event of blade actuator fault by redistributing the lost torque due to erroneous pitch position into non-faulty blade actuators. The effectiveness of the proposed method is demonstrated through simulations with a benchmark model of the wind turbine.

A Robust Sensor and Actuator Fault Tolerant Control Scheme for Nonlinear System

“…The time derivative of Lyapunov function (12) after substituting the dynamics of error system (8) gives…”

“…In [7], a Polynomial Fuzzy Unknown Input Observer (PFUIO) is proposed to estimate sensor and actuator faults to get the desired performance and avoid system instability. An active FTC technique for wind turbine systems with sensor and actuator faults is discussed in [8] using robust dynamic inversion observer and control allocation. Sliding mode control (SMC) has been employed in a range of nonlinear systems, and it is a promising option for coping with actuator failures and model uncertainties.…”