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@article{IJAMCS_2019_29_4_a9, author = {Byrski, Witold and Drapa{\l}a, Micha{\l} and Byrski, J\k{e}drzej}, title = {An adaptive identification method based on the modulating functions technique and exact state observers for modeling and simulation of a nonlinear {MISO} glass melting process}, journal = {International Journal of Applied Mathematics and Computer Science}, pages = {739--757}, publisher = {mathdoc}, volume = {29}, number = {4}, year = {2019}, language = {en}, url = {http://geodesic.mathdoc.fr/item/IJAMCS_2019_29_4_a9/} }
TY - JOUR AU - Byrski, Witold AU - Drapała, Michał AU - Byrski, Jędrzej TI - An adaptive identification method based on the modulating functions technique and exact state observers for modeling and simulation of a nonlinear MISO glass melting process JO - International Journal of Applied Mathematics and Computer Science PY - 2019 SP - 739 EP - 757 VL - 29 IS - 4 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/IJAMCS_2019_29_4_a9/ LA - en ID - IJAMCS_2019_29_4_a9 ER -
%0 Journal Article %A Byrski, Witold %A Drapała, Michał %A Byrski, Jędrzej %T An adaptive identification method based on the modulating functions technique and exact state observers for modeling and simulation of a nonlinear MISO glass melting process %J International Journal of Applied Mathematics and Computer Science %D 2019 %P 739-757 %V 29 %N 4 %I mathdoc %U http://geodesic.mathdoc.fr/item/IJAMCS_2019_29_4_a9/ %G en %F IJAMCS_2019_29_4_a9
Byrski, Witold; Drapała, Michał; Byrski, Jędrzej. An adaptive identification method based on the modulating functions technique and exact state observers for modeling and simulation of a nonlinear MISO glass melting process. International Journal of Applied Mathematics and Computer Science, Tome 29 (2019) no. 4, pp. 739-757. http://geodesic.mathdoc.fr/item/IJAMCS_2019_29_4_a9/
[1] Asiri, S.M. and Laleg-Kirati, T. (2017). Modulating functions-based method for parameters and source estimation in one-dimensional partial differential equations, Inverse Problems in Science and Engineering 25(8): 1191–1215.
[2] Ayla, L. and Solis, J. (1991). Structured logic control in glass preparation processes, IEEE Transactions on Industry Applications 27(1): 108–111.
[3] Balestrino, A., Landi, A. and Sani, L. (2000a). Identification of Hammerstein systems with input/output time delay via modulating functions, IFAC Proceedings Volumes 33(23): 199–203.
[4] Balestrino, A., Landi, A. and Sani, L. (2000b). Parameter identification of continuous systems with multiple-input time delays via modulating functions, IEE Proceedings: Control Theory and Applications 147(1): 19–27.
[5] Byrski, J. and Byrski, W. (2012). The role of parameter constraints in EE and OE methods for optimal identification of continuous LTI models, International Journal of Applied Mathematics and Computer Science 22(2): 379–388, DOI: 10.2478/v10006-012-0028-3.
[6] Byrski, J. and Byrski, W. (2016). A double window state observer for detection and isolation of abrupt changes in parameters, International Journal of Applied Mathematics and Computer Science 26(3): 585–602, DOI: 10.1515/amcs-2016-0041.
[7] Byrski, J. and Byrski, W. (2018). An optimal identification of the input-output disturbances in linear dynamic systems by the use of the exact observation of the state, Mathematical Problems in Engineering: 1–15, Article ID 8048567, DOI: 10.1155/2018/8048567.
[8] Byrski, W. and Fuksa, S. (1995). Optimal identification of continuous systems in L2 space by the use of compact support filter, International Journal of Modelling Simulation 15(4): 125–131.
[9] Byrski, W. and Kubiński, R. (1997). The convolution method for optimal identification generalized to MIMO continuous systems, Modelling, Identification and Control: Proceedings of the 16th IASTED International Conference, Innsbruck, Austria, pp. 44–47.
[10] Cieza, O.B., Tafur, J.C. and Reger, J. (2014). Frequency domain modulating functions for continuous-time identification of linear and nonlinear systems, 16th Latinamerican Control Conference, At Quintana Roo, Mexico, pp. 690–695.
[11] Co, T. and Ydstie, B. (1990). System identification using modulating functions and fast Fourier transforms, Computers Chemical Engineering 14(10): 1051–1066.
[12] Gough, B.P. and Matovich, D. (1997). Predictive-adaptive temperature control of molten glass, IEEE Industry Applications Society Dynamic Modeling Control Applications for Industry Workshop, Vancouver, BC, Canada, pp. 51–55.
[13] Grega, W., Piłat, A. and Tutaj, A. (2015). Modelling of the glass melting process for real-time implementation, International Journal of Modeling and Optimization 5(6): 366–373.
[14] Grega, W., Tutaj, A., Klemiato, M. and Byrski, W. (2016). Comparison of real-time industrial process control solutions: Glass melting case study, 21st International Conference on Methods and Models in Automation and Robotics (MMAR), Międzyzdroje, Poland, pp. 122–127.
[15] Janiczek, T. (2010). Generalization of the modulating functions method into the fractional differential equations, Bulletin of the Polish Academy of Sciences: Technical Sciences 58(4): 593–599.
[16] Jouffroy, J. and Reger, J. (2015). Finite-time simultaneous parameter and state estimation using modulating functions, IEEE Conference on Control Applications (CCA), Sydney, NSW, Australia, pp. 394–399.
[17] Khoury, R. and Harder, D. (2016). Numerical Methods and Modelling for Engineering, Springer, Cham.
[18] Kozłowski, J. and Kowalczuk, Z. (2015). On-line parameter and delay estimation of continuous-time dynamic systems, International Journal of Applied Mathematics and Computer Science 25(2): 223–232, DOI: 10.1515/amcs-2015-0017.
[19] Maletinsky, V. (1979). Identification of continuous dynamical systems with spline-type modulating functions method, IFAC Proceedings Volumes 12(8): 275–281.
[20] Pearson, A., Shen, Y. and Klein, V. (1994). Application of Fourier modulating functions to parameter estimation of a multivariable linear differential system, IFAC Proceedings Volumes 27(8): 1013–1018.
[21] Preisig, H. and Rippin, D. (1993). Theory and application of the modulating function method. I: Review and theory of the method and theory of the spline-type modulating functions, Computers Chemical Engineering 17(1): 1–16.
[22] Rao, G.P., Diekmann, K. and Unbenhauen, H. (1984). Parameter estimation in large scale interconnected systems, IFAC Proceedings Volumes 17(2): 729–733.
[23] Rao, G.P. and Sivakumar, G. (1979). Identification of deterministic time-lag systems, IEEE Transactions on Automatic Control 21(4): 527–529.
[24] Rao, G.P. and Unbehauen, G. (2006). Identification of continous-time systems, IEE Proceedings: Control Theory and Applications 153(2): 185–220.
[25] Shinbrot, M. (1957). On the analysis of linear and nonlinear systems, Transactions of the American Society of Mechanical Engineers: Journal of Basic Engineering 79: 547–552.
[26] Wang, Q., Chalaye, G., Thomas, G. and Gilles, G. (1997). Predictive control of a glass process, Control Engineering Practice 5(2): 167–173.