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Advances in the Control of Markov Jump Linear Systems with No Mode Observation
ISBN-13:
9783319398358
Veröffentl:
2016
Einband:
eBook
Seiten:
48
Autor:
Alessandro N. Vargas
Serie:
SpringerBriefs in Electrical and Computer Engineering SpringerBriefs in Control, Automation and Robotics
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:
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.
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.
Preliminaries.- Finite-Time Control Problem.- Approximation of the Optimal Long-Run Average-Cost Control Problem.- References.