rSOESGOPE Method Applied to Four-Tank System Modeling

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

  • Accacio Ferreira Dos Santos Neto
  • Murillo Ferreira Dos Santos
  • Leonardo De Mello Honorio
  • Paolo Mercorelli

It's known that the design of identification signals plays a fundamental role in the estimation quality of dynamic systems models. Well-designed signals are able to excite the system's dynamics to be later identified and represented in a model. This work presents the application of the rSOESGOPE (robust Sub-Optimal Excitation Signal Generation and Optimal Parameter Estimation) Method, which proposes the identification of robust parametric models from the use of multiple identification signals. In this perspective, the identification experiment is composed of optimized signals of the type Amplitude-modulated Pseudo Random Binary Signal (APRBS), designed by an approach composed of the Particle Swarm Optimization (PSO) and by the Interior-Point Method (IPM). To verify the effectiveness of the methodology, it was decided to study the classic problem of modeling the four-tank system, investigating the use of multiple optimized identification signals.

Original languageEnglish
Title of host publicationProceedings of the 2023 24th International Carpathian Control Conference, ICCC 2023
EditorsDaniel Drotos, Rabab Benotsmane, Attila Karoly Varga, Attila Trohak, Jozsef Vasarhelyi
Number of pages6
PublisherInstitute of Electrical and Electronics Engineers Inc.
Publication date12.06.2023
Pages141-146
ISBN (print)979-8-3503-1023-8
ISBN (electronic)979-8-3503-1022-1
DOIs
Publication statusPublished - 12.06.2023
Event24th International Carpathian Control Conference - Sinaia, Romania
Duration: 12.05.202314.05.2023
Conference number: 24

Bibliographical note

Funding Information:
The author would like to thank CEFET-MG and the Le-uphana University of Lüneburg for their financial support.

Publisher Copyright:
© 2023 IEEE.

    Research areas

  • Four-Tank System, Identification Signals Design, Optimization, Robust Parameter Estimation, System Identification
  • Engineering