Ellipsoidal constrained state estimation in presence of bounded disturbances

Yasmina Becis-Aubry

This contribution proposes a recursive, input-to-state stable and ready-to-use online algorithm for the state estimation of linear discrete-time systems with unknown but bounded disturbances corrupting both the state and the sporadic measurement vectors and subject to linear inequality and equality constraints on the state vector. Two set representation techniques are used: the state vector is characterized by an ellipsoid whereas the disturbances vectors are bounded by possibly degenerate zonotopes. The proposed algorithm is decomposed into two steps: time updating and observation updating that uses a switching estimation gain.

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