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

5 Citations (Scopus)
1 Downloads (Pure)


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
Publication statusPublished - 26 Nov 2019
EventASME 2019 Dynamic Systems and Control Conference - Park City, Utah, United States
Duration: 8 Oct 201911 Oct 2019


ConferenceASME 2019 Dynamic Systems and Control Conference
Country/TerritoryUnited States


  • 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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