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The paper presents the fault isolation method for linear systems taking into account the residual dynamics. The method is based on the analysis of the sequence of observed symptoms assuming the residual models. Additionally, the method of designing the secondary residuals that allows to achieve particular symptom sequence for particular fault is proposed. Described methods are illustrated with a simple...
The growing complexity of the control systems and the increased use of nonlinear models cause a dramatic increase in the computational requirements of MPCs. Therefore, more computationally efficient MPC are needed. This paper presents a two-phase MPC approach for decreasing computational demand without sacrificing its efficiency. The first phase of the MPC treats the input variables as independent...
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...
This paper deals with a fault detection method taking model uncertainties described by bounded variables into account. This problem is treated as an interval Constraint Satisfaction Problem (CSP) whose relations depend on both sought unknown variables and on uncertain model parameters belonging to interval supports. A set-membership inversion method is used for solving this interval CSP. An analysis...
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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