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2015 | 25 | 2 | 223-232
Tytuł artykułu

On-line parameter and delay estimation of continuous-time dynamic systems

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The problem of on-line identification of non-stationary delay systems is considered. The dynamics of supervised industrial processes are usually modeled by ordinary differential equations. Discrete-time mechanizations of continuous-time process models are implemented with the use of dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures mechanized in recursive forms are applied for simultaneous identification of input delay and spectral parameters of the system models. The performance of the proposed estimation algorithms is verified in an illustrative numerical simulation study.
Rocznik
Tom
25
Numer
2
Strony
223-232
Opis fizyczny
Daty
wydano
2015
poprawiono
2014-06-15
poprawiono
2014-09-16
otrzymano
2014-11-03
Twórcy
  • Department of Robotics and Decision Systems, Gdańsk University of Technology, Narutowicza 11/12, 80-233 Gdańsk, Poland
  • Department of Robotics and Decision Systems, Gdańsk University of Technology, Narutowicza 11/12, 80-233 Gdańsk, Poland
Bibliografia
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  • Goldberg, D.E. (1989). Genetic Algorithms in Search, Opimization and Machine Learning, Addison-Wesley, Reading, MA.
  • Ikonen, E., Najim, K. and Kortela, U. (1999). Identification of non-linear processes using steady-state models with linear FIR dynamics, 14th IFAC World Congress, Beijing, China, pp. 49-54.
  • Inoue, K., Kumamaru, K., Nakahashi, Y., Nakamura, H. and Uchida, M. (1994). A quick identification method of continuous-time nonlinear systems and its application to power plant control, 10th IFAC Symposium on System Identification, Copenhagen, Denmark, Vol. 1, pp. 319-324.
  • Janiszowski, K.B. (1998). To estimation in sense of the least sum of absolute errors, 5th International Symposium on Methods and Models in Automation and Robotics, MMAR, Międzyzdroje, Poland, Vol. 2, pp. 583-588.
  • Johansson, R. (1994). Identification of continuous-time models, IEEE Transactions on Signal Processing 42(4): 887-897.
  • Kowalczuk, Z. (1991). On discretization of continuous-time state-space models: A stable normal approach, IEEE Transactions on Circuits and Systems 38(12): 1460-14770.
  • Kowalczuk, Z. (1993). Discrete approximation of continuous-time systems-a survey, IEE Proceedings G: Circuits, Devices and Systems 140(4): 264-278.
  • Kowalczuk, Z. (1995). Discrete-time realization of online continuous-time estimation algorithms, Control and Computers 23(2): 33-37.
  • Kowalczuk, Z. and Kozłowski, J. (2000). Continuous-time approaches to identification of continuous-time systems, Automatica 36(8): 1229-1236.
  • Kowalczuk, Z. and Kozłowski, J. (2011). Non-quadratic quality criteria in parameter estimation of continuous-time models, IET Control Theory and Applications 5(13): 1494-1508.
  • Kozłowski, J. and Kowalczuk, Z. (2007). Robust to measurement faults, parameter estimation algorithms in problems of systems diagnostics, in Z. Kowalczuk and B. Wiszniewski (Eds.), Intelligent Information Extraction for Diagnostic Purposes, Pomorskie Wydawnictwo Naukowo-Techniczne, Gdańsk, pp. 221-240, (in Polish).
  • Kozłowski, J. and Kowalczuk, Z. (2009). Continuous-time delay system identification insensitive to measurement faults, in Z. Kowalczuk (Ed.), Diagnosis of Processes and Systems, Pomorskie Wydawnictwo Naukowo-Techniczne, Gdańsk, Chapter 15, pp. 177-184.
  • Ljung, L. (1987). System Identification: Theory for the User, Prentice-Hall, Upper Saddle River, NJ.
  • Middleton, R.H. and Goodwin, G.C. (1990). Digital Control and Estimation. A Unified Approach, Prentice-Hall, Upper Saddle River, NJ.
  • Mzyk, G. (2007). Generalized kernel regression estimate for the identification of Hammerstein systems, International Journal of Applied Mathematics and Computer Science 17(2): 189-197, DOI: 10.2478/v10006-007-0018-z.
  • Sagara, S., Yang, Z.J. and Wada, K. (1991). Identification of continuous systems using digital low-pass filters, International Journal of Systems Science 22(7): 1159-1176.
  • Sagara, S. and Zhao, Z.Y. (1989). Recursive identification of transfer function matrix in continuous systems via linear integral filter, International Journal of Control 50(2): 457-477.
  • Sagara, S. and Zhao, Z.Y. (1990). Identification of system parameters in distributed parameter systems, 11th IFAC World Congress, Tallinn, Estonia, pp. 471-476.
  • Schoukens, J. (1990). Modeling of continuous time systems using a discrete time representation, Automatica 26(3): 579-583.
  • Schoukens, J., Pintelon, R. and Guillaume, P. (1994). On the advantages of periodic excitations in system identification, 10th IFAC Symposium on System Identification, Copenhagen, Denmark, Vol. 3, pp. 153-158.
  • Söderström, T. and Stoica, P. (1981). Comparison of some instrumental variable methods-consistency and accuracy aspects, Automatica 17(1): 101-115.
  • Stoica, P. and Söderström, T. (1983). Optimal instrumental-variable methods for identification of multivariable linear systems, Automatica 19(4): 425-429.
  • Uciński, D. and Patan, M. (2010). Sensor network design for the estimation of spatially distributed processes, International Journal of Applied Mathematics and Computer Science 20(3): 459-481, DOI: 10.2478/v10006-010-0034-2.
  • Unbehauen, H. and Rao, G.P. (1990). Continuous-time approaches to system identification-a survey, Automatica 26(1): 23-35.
  • Unbehauen, H. and Rao, G.P. (1997). Identification of continuous-time systems: A tutorial, 11th IFAC Symposium on System Identification, Kitakyushu, Japan, Vol. 3, pp. 1023-1049.
  • Willis, M.J., Montague, G.A., Di Massimo, C., Tham, M.T. and Morris, A.J. (1992). Artificial neural networks in process estimation and control, Automatica 28(6): 1181-1188.
  • Young, P. (1981). Parameter estimation for continuous-time models-a survey, Automatica 17(1): 23-39.
  • Zhao, Z.Y. and Sagara, S. (1991). Consistent estimation of time delay in continuous-time systems, Transactions of the Society of Instrument and Control Engineers 27(1): 64-69.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
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