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

By: Contributor(s): Material type: TextTextSeries: SpringerBriefs in Electrical and Computer EngineeringPublisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: V, 48 p. 8 illus., 6 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319398358
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 629.8 23
Online resources:
Contents:
Preliminaries -- Finite-Time Control Problem -- Approximation of the Optimal Long-Run Average-Cost Control Problem -- References.
In: Springer eBooksSummary: 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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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.