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This paper proposes new sensor fault detection algorithms for linear discrete-time systems with bounded perturbations and bounded measurement noise. This fault detection technique is based on a zonotopic set-membership estimation method. The first proposed fault detection algorithm allows to detect the presence of a fault. A second algorithm leading to guaranteed state estimation in the presence of...
This paper presents an improved approach for guaranteed state estimation combining set-membership estimation techniques based on zonotopes and ellipsoids, applied on linear discrete-time systems with unknown but bounded perturbations and noises. The proposed approach starts with a zonotopic approximation and continues with an ellipsoidal approximation; this allows to manage the trade-off between the...
This paper presents an improved technique for guaranteed zonotopic state estimation of Multi-Output discrete-time linear-time invariant systems subject to unknown but bounded disturbances and measurement noises, in the presence of interval uncertainties. The estimation procedure is based on the minimization of the P-radius of the zonotopic state estimation domain, which guarantees the non-increasing...
This paper presents an improved method for guaranteed state estimation of discrete-time linear-time varying systems affected by disturbances, noises and structured uncertainties modeled as interval uncertainties. Under the hypothesis that the disturbances and the noises are bounded, a zonotopic outer approximation of the state estimation domain is computed offering good performance and low complexity...
This paper proposes an approach to deal with the problem of robust output feedback model predictive control for linear discrete-time systems subject to state and input constraints, in the presence of unknown but bounded disturbances and measurement noises. The estimation of the states is built using a zonotopic set-membership estimation. This set is time-decreasing and is computed off-line as the...
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