Conference
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Optimal input design for on-line identification: a coupled observer-MPC approach

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Optimal input design for on-line identification: a coupled observer-MPC approach
Συγγραφείς: Flila, Saida, Dufour, Pascal, Hammouri, Hassan
Συνεισφορές: Laboratoire d'automatique et de génie des procédés (LAGEP), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Centre National de la Recherche Scientifique (CNRS)
Πηγή: Proceedings of the 17th International Federation of Automatic Control (IFAC) World Congress 2008 ; International Federation of Automatic Control (IFAC) World Congress ; https://hal.science/hal-00352751 ; International Federation of Automatic Control (IFAC) World Congress, Jul 2008, Seoul, South Korea. Paper 1722, pp. 11457-11462, ⟨10.3182/20080706-5-KR-1001.1722⟩
Στοιχεία εκδότη: CCSD
Έτος έκδοσης: 2008
Συλλογή: HAL Lyon 1 (University Claude Bernard Lyon 1)
Θεματικοί όροι: nonlinear observer and filter design, design and control, identification for control, model predictive optimization-based control, [SPI.AUTO]Engineering Sciences [physics]/Automatic, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering
Θέμα γεωγραφικό: Seoul, South Korea
Περιγραφή: The authors acknowledge IFAC for their copyright policies & self-archiving. More open archives publications of Pascal Dufour are available on: http://hal.archives-ouvertes.fr/DUFOUR-PASCAL-C-3926-2008 ; International audience ; This paper presents a parametric sensitivity based controller for on line optimal model parameter identification using constrained closed loop control tools and an observer. In optimal input design problem, analytical solution exists for few particular cases based on a relatively simple model. The approach proposed here may be used for a process based on a continuous model in the time domain, with two assumptions on the observability and the general structure of the model. The new proposed approach is to solve a model predictive control problem coupled with an on line process parameter estimation at each time using an observer. A dynamic parametric sensitivity model (derived from the process model) is also used on line to get the parametric sensitivity that has to be optimized. Both optimal input and estimated model parameter are therefore obtained on line. The case study presented here is a powder coating curing process where the main thermal parameter to identify influences the powder curing. First simulation results show here the efficiency of the approach in the control software (MPC@CB) developed under Matlab.
Τύπος εγγράφου: conference object
Γλώσσα: English
DOI: 10.3182/20080706-5-KR-1001.1722
Διαθεσιμότητα: https://hal.science/hal-00352751
https://hal.science/hal-00352751v2/document
https://hal.science/hal-00352751v2/file/fli08-IFAC-WC-Seoul-11457-11462-paper.pdf
https://doi.org/10.3182/20080706-5-KR-1001.1722
Rights: https://about.hal.science/hal-authorisation-v1/ ; info:eu-repo/semantics/OpenAccess
Αριθμός Καταχώρησης: edsbas.FF80067F
Βάση Δεδομένων: BASE
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  Data: Laboratoire d'automatique et de génie des procédés (LAGEP)<br />Université Claude Bernard Lyon 1 (UCBL)<br />Université de Lyon-Université de Lyon-École Supérieure de Chimie Physique Électronique de Lyon (CPE)-Centre National de la Recherche Scientifique (CNRS)
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  Data: Proceedings of the 17th International Federation of Automatic Control (IFAC) World Congress 2008 ; International Federation of Automatic Control (IFAC) World Congress ; https://hal.science/hal-00352751 ; International Federation of Automatic Control (IFAC) World Congress, Jul 2008, Seoul, South Korea. Paper 1722, pp. 11457-11462, ⟨10.3182/20080706-5-KR-1001.1722⟩
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  Data: The authors acknowledge IFAC for their copyright policies & self-archiving. More open archives publications of Pascal Dufour are available on: http://hal.archives-ouvertes.fr/DUFOUR-PASCAL-C-3926-2008 ; International audience ; This paper presents a parametric sensitivity based controller for on line optimal model parameter identification using constrained closed loop control tools and an observer. In optimal input design problem, analytical solution exists for few particular cases based on a relatively simple model. The approach proposed here may be used for a process based on a continuous model in the time domain, with two assumptions on the observability and the general structure of the model. The new proposed approach is to solve a model predictive control problem coupled with an on line process parameter estimation at each time using an observer. A dynamic parametric sensitivity model (derived from the process model) is also used on line to get the parametric sensitivity that has to be optimized. Both optimal input and estimated model parameter are therefore obtained on line. The case study presented here is a powder coating curing process where the main thermal parameter to identify influences the powder curing. First simulation results show here the efficiency of the approach in the control software (MPC@CB) developed under Matlab.
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      – SubjectFull: nonlinear observer and filter design
        Type: general
      – SubjectFull: design and control
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      – SubjectFull: identification for control
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      – TitleFull: Optimal input design for on-line identification: a coupled observer-MPC approach
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