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Randomized Algorithms for Analysis and Control of Uncertain Systems pp 147–163Cite as

Sequential Methods for Probabilistic Design

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Part of the book series: Communications and Control Engineering ((CCE))

Abstract

This chapter studies sequential algorithms for control design of uncertain systems with probabilistic techniques. We introduce a unifying theoretical framework that encompasses most of the sequential algorithms for feasibility that appeared in the literature. In particular, under a convexity assumption in the design parameters, we develop stochastic approximation algorithms that return a so-called reliable design. The notions of probabilistic oracle and update rules are also formally introduced. Gradient algorithms and localization methods are discussed in detail.

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Authors and Affiliations

  1. CNR - IEIIT, Politecnico di Torino, Turin, Italy

    Roberto Tempo & Fabrizio Dabbene

  2. Dip. Automatica e Informatica, Politecnico di Torino, Turin, Italy

    Giuseppe Calafiore

Authors
  1. Roberto Tempo
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  2. Giuseppe Calafiore
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  3. Fabrizio Dabbene
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Tempo, R., Calafiore, G., Dabbene, F. (2013). Sequential Methods for Probabilistic Design. In: Randomized Algorithms for Analysis and Control of Uncertain Systems. Communications and Control Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-4610-0_11

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  • DOI: https://doi.org/10.1007/978-1-4471-4610-0_11

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4609-4

  • Online ISBN: 978-1-4471-4610-0

  • eBook Packages: EngineeringEngineering (R0)

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