Ellipsoidal constrained state estimation in presence of bounded disturbances

TL;DR

This paper introduces a recursive, efficient online method for ellipsoidal state estimation in linear discrete-time systems with bounded disturbances, ensuring stability and accommodating sporadic measurements with constraints.

Contribution

It presents a novel recursive algorithm for ellipsoidal state estimation that handles bounded disturbances and constraints in a computationally efficient manner.

Findings

Ensures input-to-state stability of the estimation error.

Handles bounded disturbances using zonotopes.

Provides a ready-to-use online estimation method.

Abstract

This contribution proposes a recursive, computationally efficient, ready-to-use, online method for the ellipsoidal state characterization for linear discrete-time models with additive unknown disturbances vectors (bounded by known possibly degenerate zonotopes) corrupting both the state difference equation and the sporadic measurement vectors, which are expressed as linear inequality and equality constraints on the state vector. The algorithm is decomposed into time updating and observation updating steps. In the latter, a suitable switching estimation gain is designed in such a way as to ensure the input-to-state stability of the estimation error.