In this paper a set-membership approach for fault detection of a benchmark wind turbine is proposed. The benchmark represents relevant fault scenarios in the control system, including sensor, actuator and system faults. In addition we also consider parameter uncertainties and uncertainties on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach is used generate a set that contains all states consistent with the past measurements and the given model of the wind turbine including uncertainties and noise. This set represents all possible states the system can be in if not faulty. If the current measurement is not consistent with this set, a fault is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness of the proposed method compared to other proposed methods applied to the same problem. An advantage of the proposed method is that there is no need for threshold design, and it does not produce positive false alarms. In the case where uncertainty on the torque lookup table is introduced, some faults are not detectable. Previous research has not addressed this uncertainty. The method proposed here requires equal or less detection time than previous results.

In this paper a new integrated observer-based fault estimation and accommodation strategy for discretetime piecewise linear (PWL) systems subject to actuator faults is proposed. A robust estimator is designed to simultaneously estimate the state of the system and the actuator fault. Then, the estimate of fault is used to compensate for the effect of the fault. By using the estimate of fault and the states, a fault tolerant controller using a PWL state feedback is designed. The observer-based fault-tolerant controller is obtained by the interconnection of the estimator and the state feedback controller. We show that separate design of the state feedback and the estimator results in the stability of the overall closed-loop system. In addition, the input-tostate stability (ISS) gain for the closed-loop system is obtained and a procedure for minimizing it is given. All of the design conditions are formulated in terms of linear matrix inequalities (LMI) which can be solved efficiently. Also, performance of the estimator and the state feedback controller are minimized by solving convex optimization problems. The efficiency of the method is demonstrated by means of a numerical example.

A complete methodology to design robust fault detection and isolation (FDI) filters and fault-tolerant control (FTC) schemes for linear parameter varying systems is proposed, with particular focus on its applicability to wind turbines. This paper takes advantage of the recent advances in model falsification using set-valued observers (SVOs) that led to the development of FDI methods for uncertain linear time-varying systems, with promising results in terms of the time required to diagnose faults. An integration of such SVO-based FDI methods with robust control synthesis is described, to deploy new FTC algorithms that are able to stabilize the plant under faulty environments. The FDI and FTC algorithms are assessed by resorting to a publicly available wind turbine benchmark model, using Monte Carlo simulation runs.

This paper proposes a new fault-tolerant control (FTC) method for discrete-time linear parameter varying (LPV) systems using a reconfiguration block. The basic idea of the method is to achieve the FTC goal without redesigning the nominal controller by inserting a reconfiguration block between the plant and the nominal controller. The reconfiguration block is realized by an LPV virtual actuator and an LPV virtual sensor. Its goal is to transform the signals from the faulty system such that its behavior is similar to that of the nominal system from the viewpoint of the controller. Furthermore, it transforms the output of the controller for the faulty system such that the stability and performance goals are preserved. Input-to-state stabilizing LPV gains of the virtual actuator and sensor are obtained by solving LMIs. We show that separate design of these gains guarantees the input-to-state stability (ISS) of the closed-loop reconfigured system. Moreover, we obtain performances in terms of the ISS gains for the virtual actuator, the virtual sensor, and their interconnection. Minimizing these performances is formulated as convex optimization problems subject to LMI constraints. Finally, the effectiveness of the method is demonstrated via a numerical example and stator current control of an induction motor. 5 708 S. M. TABATABAEIPOUR, J. STOUSTRUP AND T. BAK PFTC solution is usually a conservative solution. Moreover, when some severe faults are taken into account, a common solution may not always exist, and if it exists, it usually yields a low performance. On the other hand, in AFTC, the controller reacts to the occurrence of faults and changes the parameters and/or the structure of the controller. A fault detection and estimation module is used to detect and estimate the fault when it occurs. Then, based on the information about the occurred fault, a supervisory controller changes the control law or the structure of the controller, in the case of severe faults, such that the faulty system with the new controller is stable and provides an acceptable performance. AFTC can usually provide a better performance because it changes or modifies the controller based on the characterizations of the occurred fault.In most of the AFTC methods developed in the literature, a specific controller is designed for each faulty case. When the fault is detected and estimated, the controller is switched to the controller designed specifically for the system subject to the detected fault. In this paper, the idea is to keep the nominal control in the loop and design a reconfiguration block, which is inserted between the faulty system and nominal system such that the overall stability of the closed-loop is preserved. This idea is depicted in Figure 1. The idea of control reconfiguration using a virtual sensor and actuator was first proposed in [6] and later in [7] for linear systems. The goal of the reconfiguration block is to transform the output of the faulty plant to an appropriate signal such that from the nominal controller's viewpoint...

Link back to DTU OrbitCitation (APA): Tabatabaeipour, M. (2013). Active fault detection and isolation of discrete-time linear time-varying systems: a set-membership approach. International Journal of Systems Science. DOI: 10.1080DOI: 10. /00207721.2013 This article was downloaded by: [ PLEASE SCROLL DOWN FOR ARTICLETaylor & Francis makes every effort to ensure the accuracy of all the information (the "Content") contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions Active fault detection and isolation (AFDI) is used for detection and isolation of faults that are hidden in the normal operation because of a low excitation signal or due to the regulatory actions of the controller. In this paper, a new AFDI method based on set-membership approaches is proposed. In set-membership approaches, instead of a point-wise estimation of the states, a set-valued estimation of them is computed. If this set becomes empty the given model of the system is not consistent with the measurements. Therefore, the model is falsified. When more than one model of the system remains un-falsified, the AFDI method is used to generate an auxiliary signal that is injected into the system for detection and isolation of faults that remain otherwise hidden or non-isolated using passive FDI (PFDI) methods. Having the set-valued estimation of the states for each model, the proposed AFDI method finds an optimal input signal that guarantees FDI in a finite time horizon. The input signal is updated at each iteration in a decreasing receding horizon manner based on the set-valued estimation of the current states and un-falsified models at the current sample time. The problem is solved by a number of linear and quadratic programming problems, which result in a computationally efficient algorithm. The method is tested on a numerical example as well as on the pitch actuator of a benchmark wind turbine.