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

  • Book
  • © 2016

Overview

Authors:
  1. Alessandro N. Vargas

    1. Electrotechnical Department, Univ. Tech. Federal do Paraná, UTFPR, Cornelio Procópio-PR, Brazil

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  2. Eduardo F. Costa

    1. Dept. Matemática Aplicada e Estatística, Universidade de São Paulo, USP, São Carlos-SP, Brazil

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  3. João B. R. do Val

    1. FEEC, Universidade Estadual de Campinas, Campinas-SP, Brazil

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  • Broadens readers’ understanding of Markov jump linear systems
  • Details recent advances in the control of stochastic systems
  • Illustrates the usefulness of Markov jump linear systems using a real-time application
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Electrical and Computer Engineering (BRIEFSELECTRIC)

Part of the book sub series: SpringerBriefs in Control, Automation and Robotics (BRIEFSCONTROL)

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Table of contents (3 chapters)

  1. Front Matter

    Pages i-v
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  2. Preliminaries

    • Alessandro N. Vargas, Eduardo F. Costa, João B. R. do Val
    Pages 1-5

  3. Finite-Time Control Problem

    • Alessandro N. Vargas, Eduardo F. Costa, João B. R. do Val
    Pages 7-33

  4. Approximation of the Optimal Long-Run Average-Cost Control Problem

    • Alessandro N. Vargas, Eduardo F. Costa, João B. R. do Val
    Pages 35-46

  5. Back Matter

    Pages 47-48
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Keywords

About this book

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.

Authors and Affiliations

  • Electrotechnical Department, Univ. Tech. Federal do Paraná, UTFPR, Cornelio Procópio-PR, Brazil

    Alessandro N. Vargas

  • Dept. Matemática Aplicada e Estatística, Universidade de São Paulo, USP, São Carlos-SP, Brazil

    Eduardo F. Costa

  • FEEC, Universidade Estadual de Campinas, Campinas-SP, Brazil

    João B. R. do Val

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