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Stochastic Adaptive Control

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Abstract

Stochastic adaptive control focuses on the control of partially known stochastic systems. These systems occurs in both continuous and discrete time and are described by Markov chains, stochastic difference equations, and stochastic differential equations. Two major goals for the solutions are self-tuning and self-optimizing. These two goals are typically determined asymptotically so that self-optimality denotes the convergence of the average costs to the optimal long-run average cost for the true system.

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Author information

Authors and Affiliations

  1. Department of Mathematics, University of Kansas, Lawrence, KS, USA

    Tyrone Duncan & Bozenna Pasik-Duncan

Authors
  1. Tyrone Duncan
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  2. Bozenna Pasik-Duncan
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Corresponding author

Correspondence to Tyrone Duncan .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, MN, USA

    Tariq Samad

Section Editor information

  1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS), Beijing, China

    Lei Guo

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Duncan, T., Pasik-Duncan, B. (2020). Stochastic Adaptive Control. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_231-2

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  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_231-2

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5102-9

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

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Chapter history

  1. Latest

    Stochastic Adaptive Control
    Published:
    07 November 2019

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_231-2

  2. Original

    Stochastic Adaptive Control
    Published:
    01 April 2014

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_231-1

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