rSOESGOPE Method Applied to Four-Tank System Modeling
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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rSOESGOPE Method Applied to Four-Tank System Modeling. / Dos Santos Neto, Accacio Ferreira; Dos Santos, Murillo Ferreira; De Mello Honorio, Leonardo et al.
Proceedings of the 2023 24th International Carpathian Control Conference, ICCC 2023. ed. / Daniel Drotos; Rabab Benotsmane; Attila Karoly Varga; Attila Trohak; Jozsef Vasarhelyi. Institute of Electrical and Electronics Engineers Inc., 2023. p. 141-146 (Proceedings of the 2023 24th International Carpathian Control Conference, ICCC 2023).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - rSOESGOPE Method Applied to Four-Tank System Modeling
AU - Dos Santos Neto, Accacio Ferreira
AU - Dos Santos, Murillo Ferreira
AU - De Mello Honorio, Leonardo
AU - Mercorelli, Paolo
N1 - Conference code: 24
PY - 2023/6/12
Y1 - 2023/6/12
N2 - 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.
AB - 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.
KW - Four-Tank System
KW - Identification Signals Design
KW - Optimization
KW - Robust Parameter Estimation
KW - System Identification
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85166477674&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/e5313ca2-9ec0-36a1-a540-e04990b81062/
U2 - 10.1109/ICCC57093.2023.10178970
DO - 10.1109/ICCC57093.2023.10178970
M3 - Article in conference proceedings
AN - SCOPUS:85166477674
SN - 979-8-3503-1023-8
T3 - Proceedings of the 2023 24th International Carpathian Control Conference, ICCC 2023
SP - 141
EP - 146
BT - Proceedings of the 2023 24th International Carpathian Control Conference, ICCC 2023
A2 - Drotos, Daniel
A2 - Benotsmane, Rabab
A2 - Varga, Attila Karoly
A2 - Trohak, Attila
A2 - Vasarhelyi, Jozsef
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th International Carpathian Control Conference
Y2 - 12 May 2023 through 14 May 2023
ER -