Fast moving horizon state estimation for discrete‐time systems with linear constraints. (16th October 2019)

• Record Type: Journal Article
• Authors: Alessandri, Angelo; Gaggero, Mauro
• Other Names: Alessandri Angelo guestEditor.; Battistelli Giorgio guestEditor.
• Is Part Of: International journal of adaptive control and signal processing. Volume 34:Number 6(2020)
• Page Start: 706
• Page End: 720
• Publication Date: 2019-10-16
• Subjects: constrained state estimation -- moving‐horizon estimation -- optimization -- stability; Adaptive control systems -- Periodicals; Adaptive signal processing -- Periodicals; 629.836
• DOI: 10.1002/acs.3054
• Languages: English
• ISSNs: 0890-6327

Abstract

Summary: Fast moving horizon state estimation for nonlinear discrete‐time systems affected by disturbances is addressed by means of imperfect optimization at each time instant based on few iterations of the gradient, conjugate gradient, and Newton algorithms. Linear constraints on the state vector are taken into account through a projection on the subspace associated with such constraints. The stability of the estimation error for the resulting scheme is proved under suitable conditions. The effectiveness of the proposed approach is showcased via simulation results in comparison with moving horizon estimation based on complete optimization and extended Kalman filtering.