Set-membership-based distributed moving horizon estimation of large-scale systems

Journal article (2022)

Authors

P. Segovia Castillo Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering
Vicenc Puig Institut de Ròbotica i Informàtica Industrial, Barcelona, Universitat Politecnica de Catalunya
Eric Duviella Université de Lille
Research Group
Transport Engineering and Logistics (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 P. Segovia Castillo, Vicenç Puig, Eric Duviella
DOI
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https://doi.org/10.1016/j.isatra.2021.10.036
Large-scale systems Community detection Distributed state estimation Moving horizon estimation Optimality condition decomposition Set-membership
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Published Date

2022

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Transport Engineering and Logistics

Abstract

This work is concerned with the design of a two-step distributed state estimation scheme for large-scale systems in the presence of unknown-but-bounded disturbances and noise. The set-membership approach is employed to construct a compact set containing the states consistent with system measurements and bounded noise and disturbances. The tightened feasible region is then provided to a moving horizon estimator that determines the optimal state estimates. Partitioning of the overall problem and coordination of the resulting subproblems are achieved using decomposition of the optimality conditions and community detection. The proposed strategy is tested on a case study based on a reactor–separator system widely used in the literature. Its performance is compared to those of centralized and distributed (without set-membership) implementations, allowing to highlight its effectiveness.