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In this paper we consider the fault isolation problem for the linear time varying systems. Our approach is based on characterization of the observability of LTV systems by Kalman's rank condition, which permits us to design fault detection filters, feeding also the derivatives of the inputs and the outputs. We prove, using a computable method, that the isolation problem can be solved by generalized...
This paper presents a dual layer approach for robust fault tolerant estimation of nonlinear processes using a combined adaptive extended Kalman filter and fault detection and filter reconfiguration. From the one hand, the filter is made robust in face of environment uncertainty using adaptive filtering. To this end, the filter identifies the measurement covariance by means of recursive estimation,...
The paper investigates the design problem for detection and isolation of faults in linear parameter varying (LPV) systems by means of dynamic inversion where the system matrix depends affinely from the parameters. A method for the construction of the inverse, relying on the concept of parameter varying invariant subspaces and related concepts of classical geometrical system theory is presented. A...
This paper investigates the detection filter design problem for the detection and isolation of faults in linear parameter varying (LPV) systems by means of dynamic inversion where the system matrix depends affinely from the parameters. A method for the construction of the inverse, relying on the concept of parameter varying invariant subspaces and related concepts of classical geometrical system theory...
The present study addresses a solution to the position and orientation estimation problem of vehicles in ad-hoc vehicle networks using decentralised filtering. Specifically, a distributed filter operating in a cooperative federated structure for enhancing the estimation accuracy of vehicles state over unreliable wireless communication networks subject to uncertain and limited measurements is proposed...
In this paper the idea of inversion-based direct input reconstruction for robust detection, separation and estimation of multiple simultaneous faults in the presence of persistent disturbances in linear dynamical systems is presented. In particular, it is shown how in a specific filtering structure a residual generator, relying on the inverse representation of the system, by means of estimation of...
The idea of inversion-based direct input reconstruction for robust detection and separation of multiple, possibly simultaneous faults in the presence of external, non-mutually separable disturbances for linear dynamical systems was presented in [1]. In this short paper this concept is pursued further: it is shown how in a specific filtering structure, relying on the inverse representation of the system,...
This paper discusses the application of the idea of federated filtering to the estimation of intrinsically nonlinear distributed systems by examining its impacts on filtering performance by using the Extended Kalman Filter (EKF) as state estimator. Specifically, the performance of the traditional centralized solution is compared with the filtering structure obtained using the federating idea, and...
In this paper a useful combination of the idea of inversion-based direct input (fault) reconstruction and Hinfin optimal filtering for robust estimation, detection and separation of multiple simultaneous faults in the presence of persistent, non-decouplable disturbances in linear dynamical systems is presented. In particular, it is shown how in a specific filtering structure, relying on the inverse...
In this paper the classical detection filter design problem is considered as an input reconstruction problem. Input reconstruction is viewed as a dynamic inversion problem. This approach is based on the existence of the left inverse and arrives at detector architectures whose outputs are the fault signals while the inputs are the measured system inputs and outputs and possibly their time derivatives...
This paper discusses the problem of designing detection filters for a class of linear time-varying systems. The basic contribution of the paper is that by, applying a time-invariant equivalent representation of the original time-varying system, it is possible to construct a detection filter such that the solution of the design problem can be solved using algebraic methods and geometric concepts similar...
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