We propose a state estimator for linear discrete-time systems composed by coupled subsystems affected by bounded disturbances. The architecture is distributed in the sense that each subsystem is equipped with a local state estimator that exploits suitable pieces of information from parent subsystems. Furthermore, each local estimator reconstructs the state of the corresponding subsystem only. Different from methods based on moving horizon estimation, our approach does not require the online solution to optimisation problems. Our state estimation scheme, which is based on the notion of practical robust positive invariance, also guarantees satisfaction of constraints on local estimation errors and it can be updated with a limited computational effort when subsystems are added or removed.

Distributed bounded-error state estimation based on practical robust positive invariance

RIVERSO, STEFANO;FERRARI TRECATE, GIANCARLO
2015-01-01

Abstract

We propose a state estimator for linear discrete-time systems composed by coupled subsystems affected by bounded disturbances. The architecture is distributed in the sense that each subsystem is equipped with a local state estimator that exploits suitable pieces of information from parent subsystems. Furthermore, each local estimator reconstructs the state of the corresponding subsystem only. Different from methods based on moving horizon estimation, our approach does not require the online solution to optimisation problems. Our state estimation scheme, which is based on the notion of practical robust positive invariance, also guarantees satisfaction of constraints on local estimation errors and it can be updated with a limited computational effort when subsystems are added or removed.
2015
The AI, Robotics & Automatic Control category is concerned with resources on the research and techniques of artificial intelligence; that is, the creation of machines that exhibit characteristics of human intelligence (e.g., efficient representation of knowledge, reasoning, deduction, problem solving, heuristics, and analysis of contradictory or ambiguous information). Related AI technologies include expert systems, fuzzy systems, natural language processing, speech and pattern recognition, computer vision, decision-support systems, knowledge-bases, and neural networks. Robotics resources are concerned with the design, construction, and operation of robots. Automatic Control resources cover the design and development of regulating processes and systems that replace the necessity of human intervention. Topics include adaptive control, robust control, discrete-event control, dynamic control, fuzzy control, and optimal control. Cybernetics resources are concerned with the control and communication within and between artificial (machine) systems and living or natural systems.
Esperti anonimi
Inglese
Internazionale
STAMPA
88
11
2277
2290
14
bounded error estimation; distributed state estimation; robust positive invariant sets;
www.tandf.co.uk/journals/titles/00207179.asp
no
3
info:eu-repo/semantics/article
262
Riverso, Stefano; Rubini, Daria; FERRARI TRECATE, Giancarlo
1 Contributo su Rivista::1.1 Articolo in rivista
none
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1105764
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