Solution of the benchmark control problem by scenario optimization

Roberto Rocchetta, Luis G. Crespo, Sean P. Kenny

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)

Abstract

This article introduces a scenario optimization framework for reliability-based design given measurements of the uncertain parameters. In contrast to traditional methods, scenario optimization makes direct use of the available data thereby eliminating the need for assuming a distribution class and estimating its hyper-parameters. Scenario theory provides formal bounds on the probabilistic performance of a design decision and certifies the system ability to comply with various requirements for future/unseen observations. This probabilistic certificate of correctness is non-asymptotic and distribution-free. Furthermore, chance-constrained optimization techniques are used to detect and eliminate the effects of outliers in the resulting optimal design. The proposed framework is exemplified on a benchmark robust control challenge problem having conflicting design objectives.
Original languageEnglish
Title of host publicationDynamic Systems and Control Conference
Number of pages8
ISBN (Electronic)978-0-7918-5915-5
DOIs
Publication statusPublished - 26 Nov 2019
EventASME 2019 Dynamic Systems and Control Conference - Park City, Utah, United States
Duration: 8 Oct 201911 Oct 2019

Conference

ConferenceASME 2019 Dynamic Systems and Control Conference
CountryUnited States
CityUtah
Period8/10/1911/10/19

Keywords

  • reliability-based optimization
  • scenario theory
  • controller design
  • probability of failure
  • oulier
  • Outlier
  • Reliability-based optimization
  • Scenario theory
  • Controller design
  • Probability of failure

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  • Cite this

    Rocchetta, R., Crespo, L. G., & Kenny, S. P. (2019). Solution of the benchmark control problem by scenario optimization. In Dynamic Systems and Control Conference [DSCC2019-8949] https://doi.org/10.1115/DSCC2019-8949