Advances in the Control of Markov Jump Linear Systems with No Mode Observation

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 applicatio...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Vargas, Alessandro N. (Autor), Costa, Eduardo F. (Autor), do Val, João B. R. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:SpringerBriefs in Control, Automation and Robotics,
Temas:
Control engineering.
System theory.
Control theory.
Probabilities.
Operator theory.
Control and Systems Theory.
Systems Theory, Control .
Probability Theory.
Operator Theory.
Acceso en línea:Texto Completo
Descripción
Sumario: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.
Descripción Física:V, 48 p. 8 illus., 6 illus. in color. online resource.
ISBN:9783319398358
ISSN:2192-6794

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