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On the infinite-dimensional model multiple-parameter estimation using feedback-relay identification test

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dc.title On the infinite-dimensional model multiple-parameter estimation using feedback-relay identification test en
dc.contributor.author Pekař, Libor
dc.contributor.author Zezulka, František
dc.contributor.author Dostálek, Petr
dc.relation.ispartof Lecture Notes in Networks and Systems
dc.identifier.issn 2367-3370 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-03-090320-6
dc.date.issued 2021
utb.relation.volume 231 LNNS
dc.citation.spage 452
dc.citation.epage 464
dc.event.title 5th Computational Methods in Systems and Software, CoMeSySo 2021
dc.event.location online
dc.event.sdate 2021-10-01
dc.event.edate 2021-10-01
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Science and Business Media Deutschland GmbH
dc.identifier.doi 10.1007/978-3-030-90321-3_37
dc.relation.uri https://link.springer.com/chapter/10.1007%2F978-3-030-90321-3_37
dc.subject infinite-dimensional model en
dc.subject initial estimation en
dc.subject Levenberg-Marquardt algorithm en
dc.subject pole assignment en
dc.subject relay-based identification en
dc.description.abstract The objective of this contribution is twofold. First, it demonstrates a case study on applying the standard single-run relay-feedback parameter identification test to a representative of infinite-dimensional systems. Namely, a delayed mathematical model of a circuit heating laboratory appliance process is used. Second, an initial estimation of the model parameters is done via the parameter identification of another – simpler – model. The transition between these two models adopts the idea of dominant spectrum assignment that is solved by using the well-established Levenberg-Marquardt algorithm. Finally, the remaining model parameters are estimated by solving another nonlinear optimization problem in the frequency domains. As transfer function denominator parameters are set independently to the numerator ones, the proposed technique significantly reduces the number of additional relay experiments. Numerical results indicate that the method needs improvements regarding time-response as well as frequency-response accuracy. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1010727
utb.identifier.obdid 43883143
utb.identifier.scopus 2-s2.0-85120685397
utb.source d-scopus
dc.date.accessioned 2021-12-22T11:51:36Z
dc.date.available 2021-12-22T11:51:36Z
dc.description.sponsorship 1170/10/2137
utb.contributor.internalauthor Pekař, Libor
utb.contributor.internalauthor Dostálek, Petr
utb.fulltext.affiliation Libor Pekař 1,2[0000-0002-2401-5886], František Zezulka1[0000-0002-4057-6018], and Petr Dostálek2 1 College of Polytechnics Jihlava, Tolstého 1556, 586 01 Jihlava, Czech Republic 2 Tomas Bata University in Zlín, nám. T. G. Masaryka 5555, 76001 Zlín, Czech Republic [email protected]
utb.fulltext.dates -
utb.fulltext.references 1. Åström, K.J., Hägglund, T.: Automatic tuning of simple regulators with specifications on phase and amplitude margins. Automatica 20(5), 645–651 (1984). 2. Dharmalingam, K., Thangavelu, T.: Parameter estimation using relay feedback. Rev. Chem. Eng. 35(4), 505-529 (2019). 3. Liu, T., Wang, Q.-G, Huang, H.P.: A tutorial review on process identification from step or relay feedback test. J. Process Control 23(10), 1597–1623 (2013). 4. Wang, Q.-G., Hang, C.C., Zou, B.: Low-order modeling from relay feedback. Ind. Eng. Chem. Res. 36(2), 375–381 (1997). 5. Ma, M.D., Zhu, X.J.: A simple auto-tuner in frequency domain. Comput. Chem. Eng. 30(4), 581–586 (2006). 6. Jeon, C.H., Cheon, Y.J., Kim, J.S., Lee, J., Sung, S.W.: Relay feedback methods combining sub-relays to reduce harmonics. J. Process. Control 20(2), 228–234 (2010). 7. Yu, C.C.: Autotuning of PID Controllers: A Relay Feedback Approach. 2nd ed., Springer, London (2006). 8. Hofreiter, M.,: Relay feedback identification with additional integrator. IFACPapersOnLine 52(13), 66-71 (2019). 9. Bi, Q., Wang, Q.-G., Hang, C.C.: Relay-based estimation of multiple points on process frequency response. Automatica 33(9), 1753–1757 (1997). 10. Hale, J.K., Lunel, S.V.: Introduction to Functional Differential Equations. Springer, New York (1993). 11. Vyhlídal, T., Zítek, P.: Control system design based on a universal first order model with time delays. Acta Polytech. 41(4-5), 49-53 (2001). 12. Pekař, L., Prokop, R.: Saturation relay vs. relay transient identification tests for a TDS model. In: Proc. 27th Eur. Conf. Model. Simul. (ECMS 2013), pp. 446-452, Alesund, Norway (2013). 13. Pekař, L.: Modeling and identification of a time-delay heat exchanger plant. In: Pekař, L. (ed.) Advanced Analytic and Control Techniques for Thermal Systems with Heat Exchangers, pp. 23-48. Academic Press (Elsevier), Cambridge, MA, USA (2020). 14. Hofreiter, M.: Fitting anisochronic models by method of moments for anisochronic control of time delay systems. Int. J. Math. Mod. Meth Appl. Sci. 10, 71-79 (2016). 15. Úředníček, Z.: Nonlinear systems-describing functions analysis and using. MATEC Web Conf. 210, 02021 (2018). 16. Ramana, K.V., Majhi, S., Gogoi, A.K.: Identification of DC–DC buck converter dynamics using relay feedback method with experimental validation. IET Circ. Devices Syst. 12(6), 777-784 (2018). 17. Pekař, L.: Root locus analysis of a retarded quasipolynomial. WSEAS Trans. Syst. Control 6(3), 79-91 (2011). 18. Marquardt, D.: An algorithm for least-squares estimation of nonlinear parameters. SIAM J. Appl. Math. 11(2), 431–441 (1963).
utb.fulltext.sponsorship This research was supported by the College of Polytechnics Jihlava, under Grant no. 1170/10/2137.
utb.scopus.affiliation College of Polytechnics Jihlava, Tolstého 1556, Jihlava, 586 01, Czech Republic; Tomas Bata University in Zlín, nám. T. G. Masaryka 5555, Zlín, 76001, Czech Republic
utb.fulltext.projects 1170/10/2137
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