Actuator Fault Diagnosis Scheme Research Articles

Adaptive unknown input observer for nonlinear systems with application to fault diagnosis

An adaptive unknown input observer for nonlinear systems whose nonlinear functions satisfy Lipschitz condition is presented. The main advantage of the proposed observer is that it is sufficient to satisfy the standard existence conditions of normal unknown input observer design. Another advantage is that it estimates both states and parameters simultaneously. So it can be very much useful for robust control and fault diagnosis. As a possible application, an actuator fault diagnosis scheme is developed for single link robot arm. Finally, numerical simulation is performed to validate the effectiveness of the proposed observer in estimating the parameter along with states.

Active Fault Tolerant Control Scheme for Satellite Attitude Systems: Multiple Actuator Faults Case

In this paper, an active fault tolerant control (FTC) design approach is proposed for the satellite attitude systems with exogenous disturbance and multiple actuator faults. Firstly, the nonlinear attitude system model of rigid satellite with multiple actuator faults is given. Next, an actuator fault diagnosis scheme, including a fault detection module and a fault estimation module, is given so as to detect the time of unknown actuator faults occurred and obtain their estimation values. Then, a terminal sliding mode-based fault tolerant attitude controller is designed using backstepping control technique, which guarantees that the closed-loop attitude systems of rigid satellite are asymptotically stable in the presence of multiple actuator faults. Numerical simulations illustrate the good performance of active FTC proposed in this study.

Fault diagnosis for flight control systems using subspace method and adaptive two-stage Kalman filter

Model-based fault diagnosis has attracted considerable attention from researchers and developers of flight control systems, thanks to its hardware simplicity and cost-effectiveness. However, the airplane model, which is adopted commonly in fault diagnosis, only exists theoretically and is linearized in approximation. For this reason, uncertainties such as system non-linearity and subjectivity will degrade the fault diagnosis results. In this paper, we propose a novel actuator fault diagnosis scheme for flight control systems based on model identification techniques. With this scheme, system identification can be achieved with a linear model that uses a closed-loop subspace model identification algorithm, and a non-linear model that uses an extended state observer and neural networks. On this basis, the current actuator fault is estimated using an adaptive two-stage Kalman filter. Finally, the non-linear six-degree-of-freedom model of a B747 airplane is simulated in the Matlab/Simulink environment, where the effectiveness of the proposed scheme is verified from fault diagnosis tests.

Robust actuator fault diagnosis scheme for satellite attitude control systems

In this paper, a robust actuator fault diagnosis scheme is investigated for satellite attitude control systems subject to model uncertainties, space disturbance torques and gyro drifts. A nonlinear unknown input observer is designed to detect the occurrence of any actuator fault. Subsequently, a bank of adaptive unknown input observers activated by the detection results are designed to isolate which actuator is faulty and then estimate of the fault parameter. Fault isolation is achieved based on the well known generalized observer strategy. The simulation on a closed-loop satellite control system with time-varying or constant actuator faults in the form of additive and multiplicative unknown dynamics demonstrates the effectiveness of the proposed robust fault diagnosis strategy.

Actuator fault diagnosis for a class of nonlinear systems and its application to a laboratory 3D crane

In this paper, an actuator fault diagnosis scheme is proposed for a class of affine nonlinear systems with both known and unknown inputs. The scheme is based on a novel input/output relation derived from the considered nonlinear systems and the use of the recently developed high-order sliding-mode robust differentiators. The main advantages of the proposed approach are that it does not require a design of nonlinear observer and applies to systems not necessarily detectable. Conditions are provided to characterize the feasibility of fault detection and isolation using the proposed scheme and the maximum number of isolatable actuator faults. The efficacy of the proposed actuator fault diagnosis approach is tested through experiments on a laboratory 3D Crane, and the experimental results show that the proposed actuator fault diagnosis approach is promising and can achieve fault detection and isolation satisfactorily.

Actuator fault diagnosis for uncertain linear systems using a high‐order sliding‐mode robust differentiator (HOSMRD)

AbstractMany observer‐based fault diagnosis strategies proposed for linear systems, subject to unknown inputs, operate based on three assumptions. The first assumption is that the system under consideration is at least detectable. The second one is that the unknown inputs satisfy certain matching conditions. The third one, which is often implicit, is that the relative degrees from the generalized input vector, including both known and unknown inputs, to the outputs are no larger than one. If none of these assumptions are met, little result exists on how to carry out fault diagnosis. The purpose of this paper is to develop a novel actuator fault diagnosis scheme for a general class of linear systems subject to unknown inputs that can work without the mentioned three assumptions. Four actuator fault diagnosis problems related to fault detection, isolation, and estimation are formulated and studied. In order to solve these problems, an input–output relation, which involves only the outputs and their higher‐order derivatives, is derived. The posed problems are solved based on this relation via utilizing both the outputs and their higher‐order derivatives. Because only the outputs are measured, higher‐order output derivatives are estimated using the recently developed high‐order sliding‐mode robust differentiators (HOSMRDs). The first two fault detection and isolation problems are answered in terms of a concept called Generalized Actuator Fault Isolation IndeX (GAFIX), and it is proved that, under the condition that the derived input–output relation is used for fault diagnosis, actuator faults are detectable if and only if GAFIX⩾1, and l actuator faults can be isolated if and only if GAFIX⩾l+1. A method which can be used to estimate the faults is proposed for the fault estimation problem. To solve the last problem, an actuator fault diagnosis scheme is designed using both the measured outputs and their estimated derivatives obtained by HOSMRDs, and is presented in steps. Finally, an example is provided to show the effectiveness of our fault diagnosis scheme in terms of fault detection, isolation, and estimation. Copyright © 2007 John Wiley & Sons, Ltd.