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A robust fault diagnosis approach is developed by incorporating a set-membership identification (SMI) method. A class of systems with linear models in the form of fault related parameters is investigated, with model uncertainties and parameter variations taken into account explicitly and treated as bounded errors. An ellipsoid bounding set-membership identification algorithm is proposed to propagate bounded uncertainties rigorously and the guaranteed feasible set of faults parameters enveloping true parameter values is given. Faults arised from abrupt parameter variations can be detected and isolated on-line by consistency check between predicted and observed parameter sets obtained in the identification procedure. The proposed approach provides the improved robustness with its ability to distinguish real faults from model uncertainties, which comes with the inherent guaranteed robustness of the set-membership framework. Efforts are also made in this work to balance between conservativeness and computation complexity of the overall algorithm. Simulation results for the mobile robot with several slipping faults scenarios demonstrate the correctness of the proposed approach for faults detection and isolation (FDI). [ABSTRACT FROM AUTHOR]

In this paper, a rapid detection and isolation scheme for oscillation faults in a distributed nonlinear system is proposed. The distributed nonlinear system considered is modeled as a set of interconnected subsystems. First, a local learning and merging method based on deterministic learning theory is proposed to obtain knowledge of the unknown interconnections and the fault functions. Second, using learned knowledge, a bank of consensus-based dynamical estimators are constructed for each subsystem, and average L1 norms of the residuals are generated to make the detection and isolation decisions. Third, a rigorous analysis for characterizing the detection and isolation capabilities of the proposed scheme is given. The attraction of the intelligence fault diagnosis approach is to give a fast response to faults using the learned knowledge and processing huge data in a dynamical and distributed manner. Simulation studies are included to demonstrate the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

This technical note investigates the development of fault detection and isolation (FDI) filters for linear impulsive systems. The concept of an unobservability subspace is introduced for linear impulsive systems and an algorithm for its construction is described. The necessary and sufficient conditions for solvability of the fundamental problem of residual generation for linear impulsive systems are obtained by utilizing our introduced unobservability subspace. Simulation results demonstrate the effectiveness of our proposed FDI strategy. [ABSTRACT FROM AUTHOR]

This paper is concerned with development of novel fault detection and isolation (FDI) strategies for the Markovian jump linear systems (MJLS's) and the MJLS's with time-delays (MJLSD's). First a geometric property that is related to the unobservable subspace of MJLS's is presented. The notion of a finite unobservable subspace is then introduced for the MJLSD's. The concept of unobservability subspace is introduced for both the MJLS's and the MJLSD's and an algorithm for its construction is described. The necessary and sufficient conditions for solvability of the fundamental problem of residual generation (FPRG) for the MJLS's are developed by utilizing our introduced unobservability subspace. Furthermore, sufficient solvability conditions of the FPRG for the MJLSD's are also derived. Finally, sufficient conditions for designing an H∞-based FDI algorithm for the MJLS's with an unknown transition matrix that are also subject to input and output disturbances are developed. [ABSTRACT FROM AUTHOR]

This paper investigates the development of fault detection and isolation (FDI) filters for distributed time-delay systems. The notion of a finite unobservability subspace is introduced for distributed time-delay systems and an algorithm for its construction is presented. A bank of residual generators is designed based on our developed geometric framework so that each residual is affected by one fault and is decoupled from the others while the H∞, norm of the transfer function between the disturbance and the residual signals are kept at less than a prespecified value. Simulation results for a combustion system in a rocket motor chamber demonstrate the effectiveness and capabilities of our proposed FDI algorithm. [ABSTRACT FROM AUTHOR]

This technical note investigates development, design and analysis of actuator Fault Detection and Isolation (FDI) filters for a network of unmanned vehicles. It is shown that actuator fault signatures in a network of unmanned vehicles are dependent and the network can be considered as an over-actuated system. An isolability index μ is defined for a family of fault signatures and a new structured residual set is developed that is selectively capable of properly detecting and isolating μ multiple faults in linear systems with dependent fault signatures, such as over-actuated systems. Our proposed algorithm is then applied to the actuator FDI problem in a network of unmanned vehicles configured according to centralized, decentralized and semi-decentralized architectures. A comparative analysis in terms of the capabilities and limitations of these architectures is performed. Simulation results presented for the formation flight of multiple satellites demonstrate the effectiveness of our proposed FDI algorithm. [ABSTRACT FROM AUTHOR]

We consider here the fault detection and isolation (FDI) problem for linear systems. We are interested in designing a set of observer-based residuals, in such a way that the transfer from the faults to the residuals is diagonal and the transfer from the disturbances to the residuals is zero. We deal with this problem when the system under consideration is structured, that is, the entries of the system matrices are either fixed zeros or free parameters. This problem can be solved in terms of the graph that can be associated in a natural way with a structured system. When the FDI solvability conditions are not satisfied, we assume that internal variables can be measured at a cost and look into the question of weather the problem is solvable with these new measurements. We give solvability conditions for a solution with a minimal number of additional sensors and among such solutions provide a minimal cost solution for the sensor location problem under consideration. We pay particular attention to the internal analysis of the system, and we propose a structural decomposition of the system associated graph based on some particular separators. This analysis leads to the definition of a reduced system. We prove that some potential additional sensors are inefficient for solving our FDI problem and that the FDI problem can be solved using only measurements on the reduced system. [ABSTRACT FROM AUTHOR]

The observer design problem is investigated in the context of linear left shift invariant discrete behaviors, whose trajectories have supports on Z+. Necessary and sufficient conditions for the existence of a dead-beat observer of some relevant variables from some measured ones, in the presence of some unmeasured (and irrelevant) variables, are introduced, and a complete parametrization of all dead-beat observers is given. Equivalent conditions for the existence of causal dead-beat observers are then derived. Finally, several classical problems addressed for state-space models, like state estimation, the design of unknown input observers or the design of fault detectors and identifiers (possibly in the presence of disturbances), are cast in this general framework, and the aforementioned equivalent conditions and parametrizations are specialized to these cases. [ABSTRACT FROM AUTHOR]

In this paper, the actuator fault diagnosis problem for a class of bilinear systems with uncertainty is discussed. The system is transformed into two different subsystems. One is not affected by actuator fault, so an adaptive observer can be designed such that, under certain conditions, the observer error dynamics is stable. The other whose states can be measured is affected by the faults. The observation scheme is then used for model-based fault diagnosis. Finally, an example of a semiactive suspension system is used to illustrate the applicability of the proposed method. [Copyright &y& Elsevier]