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Probabilistic reachable and invariant sets for linear systems with correlated disturbance

Authors :
Teodoro Alamo
Mirko Fiacchini
GIPSA - Modelling and Optimal Decision for Uncertain Systems (GIPSA-MODUS)
GIPSA Pôle Automatique et Diagnostic (GIPSA-PAD)
Grenoble Images Parole Signal Automatique (GIPSA-lab)
Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab)
Université Grenoble Alpes (UGA)
Departamento de Ingenieria de Sistemas y Automatica [Sevilla] (ISA)
ANR-11-LABX-0025,PERSYVAL-lab,Systemes et Algorithmes Pervasifs au confluent des mondes physique et numérique(2011)
Universidad de Sevilla
Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
Universidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Control
Source :
Automatica, Automatica, Elsevier, 2021, 132, pp.109808. ⟨10.1016/j.automatica.2021.109808⟩, Automatica, Elsevier, In press, idUS. Depósito de Investigación de la Universidad de Sevilla, instname
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

Paper on stochastic invariance; International audience; In this paper a constructive method to determine and compute probabilistic reachable and invariant sets for linear discrete-time systems, excited by a stochastic disturbance, is presented. The samples of the disturbance signal are not assumed to be uncorrelated, only bounds on the mean and the covariance matrices are supposed to be known. This allows to consider nonlinear stochastic systems approximations and the effect of nonlinear filters on the disturbance. The correlation bound concept is introduced and employed to determine probabilistic reachable sets and probabilistic invariant sets. Constructive methods for their computation, based on convex optimization, are given.

Details

Language :
English
ISSN :
00051098
Database :
OpenAIRE
Journal :
Automatica, Automatica, Elsevier, 2021, 132, pp.109808. ⟨10.1016/j.automatica.2021.109808⟩, Automatica, Elsevier, In press, idUS. Depósito de Investigación de la Universidad de Sevilla, instname
Accession number :
edsair.doi.dedup.....c24d9418d66b9bedcd8096acce07460e