Robust stability of stochastic systems with varying delays: application to RLC circuit with intermittent closed-loop

This paper characterizes the robust second-moment stability of stochastic linear systems subject to varying delays. The delays assume a particular form suitable to represent packet loss in networked control systems, under the zero-order hold feedback. The proposed robust stability condition requires...

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Detalles Bibliográficos
Autores: El Hamdi, Issam, Vargas, Alessandro N., Hassane Bouzahir, Hassane, Bouzahir, Oliveira, Ricardo C.L.F., Acho Zuppa, Leonardo|||0000-0002-4965-1133
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/350730
Acceso en línea:https://hdl.handle.net/2117/350730
https://dx.doi.org/10.1016/j.amc.2021.126541
Access Level:acceso abierto
Palabra clave:Markov processes
Electric circuits
Distribution (Probability theory)
Stochastic systems
Markov jump linear systems
Stochastic stability
Robust stability
Packet dropout
RLC circuits
Markov, Processos de
Circuits elèctrics
Distribució (Teoria de la probabilitat)
Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat
Descripción
Sumario:This paper characterizes the robust second-moment stability of stochastic linear systems subject to varying delays. The delays assume a particular form suitable to represent packet loss in networked control systems, under the zero-order hold feedback. The proposed robust stability condition requires checking the spectral radius of an appropriate matrix that that depends on uncertain parameters belonging to a polytope. Due to this polytope’s dependence, checking the spectral radius is difficult from the numerical viewpoint. As an attempt to solve the problem, we convert the polytope-based condition into a randomized approach. Namely, we present probability bounds that help us certificate the robust second-moment stability under high probability. A real-time electronic application illustrates the potential benefits of our approach.