Direct data-driven design of switching controllers for constrained systems

Andrea Sassella, Valentina Breschi, Simone Formentin

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

Abstract

This paper presents a hierarchical structure to directly design controllers for (possibly nonlinear) constrained systems. The proposed architecture combines the advantages of an inner data-driven switching controller designed to achieve a predefined closed-loop behavior and an outer model predictive controller, which is used as a reference governor. These design choices enable us to avoid the identification step typical of model-based approaches while exploiting the ability of model predictive controllers to handle constraints and optimize the closed-loop performance. As a proof of concept, a benchmark simulation example is used to demonstrate the effectiveness of the proposed strategy.
Original languageEnglish
Title of host publication2021 American Control Conference, ACC 2021
PublisherInstitute of Electrical and Electronics Engineers
Pages2355-2360
Number of pages6
ISBN (Electronic)978-1-6654-4197-1
DOIs
Publication statusPublished - 28 Jul 2021
Externally publishedYes
Event2021 American Control Conference, ACC 2021 - Virtual, Virtual, New Orleans, United States
Duration: 25 May 202128 May 2021
http://acc2021.a2c2.org/

Conference

Conference2021 American Control Conference, ACC 2021
Abbreviated titleACC 2021
Country/TerritoryUnited States
CityVirtual, New Orleans
Period25/05/2128/05/21
Internet address

Keywords

  • Data-driven control
  • Predictive models
  • Switching systems
  • Reference governor

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