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For sequential jumps detection, isolation and estimation in discrete-time stochastic linear systems, Willsky and Jones. have developed the Generalized Likelihood Ratio (GLR) test. After each detection and isolation of one jump, the treatment of another possible jump is obtained by a direct state estimate and covariance incrementation of the Kalman filter originally designed on the jump-free system...
Significant research has been carried out over the past three decades in the area of fault tolerant control. Most methods available in the chemical engineering literature are capable of detecting, identifying, estimating and accommodating faults for nonlinear processes with continuous states without state dependent and controlled switching. This work is aimed at developing a method for diagnosing...
In this paper, the sliding mode approach is used to control of a quadrotor unmanned aerial vehicle (UAV) in the presence of external disturbance and actuator fault. Fault detection unit can detect the actuator fault using a state estimator. Then it reconfigures the structure of controller such that some control performance is achieved. The proposed control structure has the advantage of disturbance...
In this work, a new fault tolerant control (FTC) methodology is proposed to deal with the potential problems due to possible fault scenarios. For this purpose, a state estimation scheme has been developed using an adaptive unscented Kalman filter (AUKF) approach. A fuzzy-based decision making (FDM) algorithm is introduced to diagnose sensor and/or actuator faults. The proposed fault detection and...
In this paper, a new approach for state filtering of dynamic stochastic discrete-time systems affected by unknown inputs is presented. The proposed state filtering scheme includes a restricted diagonal detection filter generating a set of minimum variance white detection signals, each of them sensitive to a particular component of the unknown input vector. After having tested the statistical effect...
This paper deals with state estimation and fault detection in the presence of unknown but bounded state perturbations and measurement noise. In this context, most available results are for linear models. Based on interval analysis, a state estimator for nonlinear dynamical systems is presented. Given the perturbation and noise bounds, the proposed method evaluates a set estimate guaranteed to contain...
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