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This paper addresses the robust (in the disturbance de-coupling sense) design problem of fault detection filters for uncertain sampled data systems. The only available signal is the output variable. A novel reduced-order unknown-input observer is proposed such that both the estimation error and the state vector vanish asymptotically, robustly with respect to disturbances affecting the continuous-time...
The design of exponentially stable interval observers is often subject to assumptions related to monotone influences in the vector field. This may lead to significant restrictions, especially when the response of systems exhibiting an oscillatory behavior should be over-approximated under uncertain inputs. In order to overcome this issue, a stable interval observer for LTI systems with bounded inputs...
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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