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Advances in the Control of Markov Jump Linear Systems with No Mode Observation / by Alessandro N Vargas, Eduardo F Costa, João B R do Val

By: Vargas, Alessandro N.
Contributor(s): SpringerLink (Online service) | Costa, Eduardo F. | do Val, João B. R.
Material type: materialTypeLabelE-bookSeries: (SpringerBriefs in Electrical and Computer Engineering, 2191-8112).Publisher: Cham : Springer International Publishing, 2016Description: 1 recurso en línea (V, 48 páginas) : 8 ilustraciones, 6 ilustraciones en color.ISBN: 9783319398358.Subject: Operadores, Teoría de | Sistemas, Teoría deDDC classification: 629.8 Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Preliminaries -- Finite-Time Control Problem -- Approximation of the Optimal Long-Run Average-Cost Control Problem -- References.
Abstract: This brief broadens readers� understanding of stochastic control by highlighting recent advances in the design of optimal control for Markov jump linear systems (MJLS). It also presents an algorithm that attempts to solve this open stochastic control problem, and provides a real-time application for controlling the speed of direct current motors, illustrating the practical usefulness of MJLS. Particularly, it offers novel insights into the control of systems when the controller does not have access to the Markovian mode.
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Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA402.3 V374 2016 EB (Browse shelf(Opens below)) .i11596764 Acceso electrónico eBOOK .i11596764
Total holds: 0

Preliminaries -- Finite-Time Control Problem -- Approximation of the Optimal Long-Run Average-Cost Control Problem -- References.

This brief broadens readers� understanding of stochastic control by highlighting recent advances in the design of optimal control for Markov jump linear systems (MJLS). It also presents an algorithm that attempts to solve this open stochastic control problem, and provides a real-time application for controlling the speed of direct current motors, illustrating the practical usefulness of MJLS. Particularly, it offers novel insights into the control of systems when the controller does not have access to the Markovian mode.

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