Fault Detection And Isolation Observers Research Articles

Event triggered [formula omitted] fault detection and isolation for T-S fuzzy systems with local nonlinear models

This paper is concerned with network-based fault detection and isolation(FDI) observer design for a class of Takagi–Sugeno (T-S) fuzzy systems with local nonlinear models. First, by combining the original system with the FDI observer, the closed-loop systems with asynchronous membership functions are modeled. Second, a new condition is introduced into the event-triggered scheme(ET scheme). This condition facilitates dealing with the asynchronous membership functions. Third, new relaxation terms are added to deal with the time delay disturbance and faults introduced by the Lyapunov–Krasovskii function(LKF) method. Then, sufficient conditions for the existence of the desired FDI observer which ensures the H−/H∞ performance are proposed. Besides, a two-step algorithm is given to co-design the parameters of the ET scheme and a bank of observers are constructed such that each of them is sensitive to particular faults. An inverted pendulum example is given to illustrate the effectiveness of the new results.

Event‐triggered fault detection and isolation for discrete‐time linear systems

In this study, the problem of event-triggered fault detection and isolation (FDI) for discrete-time linear time-invariant systems is considered. Using a Leunberger observer as the residual generator, a multi-objective formulation of the FDI problem is presented based on l 1 , H _ and H ∞ performance indices. For each performance index, sufficient conditions for the design of FDI observer are presented based on linear matrix inequalities (LMIs). To reduce the conservativeness of the multi-objective problem, extended LMIs are used to eliminate the couplings of Lyapunov matrices with the system state space matrices. It is shown that through an event-triggered data transmission mechanism, the amount of data that is sent to the FDI module is significantly decreased. Simulation results corresponding to a remotely operated vehicle demonstrate the effectiveness and capabilities of the proposed design methodology.

Sampled-data [formula omitted] fault detection and isolation for nonlinear systems in T–S form: An approximate model approach

A direct discrete-time design methodology for the sampled-data fault detection and isolation (FDI) problem is proposed for a nonlinear system in Takagi–Sugeno form. The generalized observer scheme is adopted, accompanied by a bank of the sensors' number of observers. A sufficient condition to find observer and residual gains, based on an accessible approximate—rather than unavailable exact—discrete-time model is proposed in terms of matrix inequalities so that it exhibits H−/H∞ performance and asymptotic stability. An algorithm involving a convex optimization is presented using the cone complementary linearization technique. We show that the FDI observer ensures (modified) H−/H∞ performance and Lagrange stability, when it is connected to the actual nonlinear system.

Fault detection and isolation for uncertain closed‐loop systems based on adaptive and switching approaches

SummaryThis paper deals with the fault detection and isolation (FDI) problem for uncertain closed‐loop systems with external disturbances and nonlinear perturbations. To address the system uncertainties and the nonlinear perturbations in different faulty models, adaptive and switching techniques are introduced to construct a bank of FDI observers, such that one of them can match the current system, and the corresponding observer estimate errors can converge asymptotically to zero. An effective FDI scheme is then presented by introducing some model‐matching indexes. Moreover, the introduced switching laws liberate the equality constraints often used in the existing FDI approaches, which are hard to satisfy if the system matrices include uncertainties. Finally, a simulation example of F/A‐18A automatic carrier landing system is used to illustrate the effectiveness of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.

Fault Detection and Isolation for a Class of Uncertain State-Feedback Fuzzy Control Systems

This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear state-feedback control systems with parameter uncertainties. First, the considered nonlinear systems are described by multiple T–S fuzzy models with uncertain grades of membership and local nonlinear parts in normal case and faulty cases. Then, a switching technique is introduced to address the uncertain grades of membership, external disturbances, local nonlinear parts, faults, and the coupling of them. In a multiple-model scheme, a bank of FDI observers are constructed, each of which is based on the T–S model that describes the system in the presence of a particular fault, such that one of them can track the current system state, and the corresponding observer estimate error can converge exponentially to zero. Finally, two examples are given to illustrate the effectiveness and advantages of the new results.

Robust fault detection and isolation for a class of uncertain single output non‐linear systems

The problem of robust fault detection and isolation (FDI) is studied for a class of uncertain single output non-linear systems with q faults. By designing a switching law, a robust state observer is developed such that its state responses can asymptotically converge to the true system states for both fault-free and faulty cases. Based on this robust state observer and other q + 1 FDI observers, an efficient scheme is presented such that the FDI can be achieved for the considered single output non-linear systems. The theoretical results are illustrated through an example of a single-link flexible joint robot.

Discontinuous dynamical systems for fault detection. A unified approach including fractional and integer order dynamics

This paper considers a discontinuous dynamical observers stack and presents its possible application in the framework of fault detection and isolation (FDI) problems. Non-standard forms for the discontinuous observer injection signals, based on second-order sliding-mode techniques with dynamical sliding manifolds, are employed in the present work. A unified treatment covering at the same time integer-order and fractional-order (FO) dynamics is developed. Appropriate non-smooth Lyapunov analysis is made to support the theoretical properties of the suggested FDI observers, which yields simple tuning formulas for the corresponding parameters. Numerical implementation aspects are discussed. Finally, simulation and experimental results are presented to support the theoretical treatment, which confirm the expected performance.

Multiobjective fault detection and isolation for flexible air-breathing hypersonic vehicle

An application of the multiobjective fault detection and isolation (FDI) approach to an air-breathing hypersonic vehicle (HSV) longitudinal dynamics subject to disturbances is presented. Maintaining sustainable and safe flight of HSV is a challenging task due to its strong coupling effects, variable operating condi- tions and possible failures of system components. A common type of system faults for aircraft including HSV is the loss of effective- ness of its actuators and sensors. To detect and isolate multiple actuator/sensor failures, a faulty linear parameter-varying (LPV) model of HSV is derived by converting actuator/system compo- nent faults into equivalent sensor faults. Then a bank of LPV FDI observers is designed to track individual fault with minimum error and suppress the effects of disturbances and other fault signals. The simulation results based on the nonlinear flexible HSV model and a nominal LPV controller demonstrate the effectiveness of the fault estimation technique for HSV.

Fault detection and isolation observers

A design of reduced-order observers is proposed for linear time-invariant systems with unknown inputs including unknown measurement disturbances. Based on the unknown-input observer design, a systematic treatment of designing fault detection and isolation (FDI) observers is provided. The core of the FDI observer design is to find an observable subsystem where the faults of interest show up and the rest of the faults disappear. The FDI observer design procedure has a clear physical meaning. Robust FDI observers for uncertain systems can also be obtained using the FDI observer design provided the uncertainties of the system can be formulated as unknown inputs. It is shown that the parity equations of another important FDI method can be generated in an elegant way using a dead-beat FDI observer scheme directly in the time domain. Examples are included to show some concepts and to illustrate the FDI observer design method.

Design of Robust Observers for Fault Isolation

Abstract This paper provides a systematic treatment of observer design for the fault detection and isolation (FDI) in linear time-invariant systems. The results of the unknown-input observer obtained recently by the authors are extended to the more general case in which the unknown disturbances are involved also in the system measurement equation. Based on these results the necessary and sufficient conditions for the existence of FDI observers are presented and the design procedure for FDI observers is given. This design procedure is simple and has a clear physical meaning. The most important feature of this method is that the original FDI observer design problem is reduced to an equivalent conventional observer design problem which can be easily dealt with following the well-known Luenberger observer theory. An example is included to illustrate the design procedure. The results presented in this paper can be used directly to the design problem of FDI observers for systems with unknown inputs.