Abstract
Modern diagnostics and control algorithms rely on physical processes models. Such models have often complicated structure and their synthesis is usually difficult. The approaches based on Partial Differential Equations (PDE) work well for simulation purposes, however their usefulness can be limited in case of industrial applications when a full set of processes data is often inaccessible. The aforementioned problem was the main motivation to propose an adaptive identification method available to work on-line based on processes data. It is based on the Modulating Functions Method (MFM) and utilizes the Exact State Observers. The method was applied for real processes data collected from the industrial glass conditioning installation. The experimental results are presented and discussed in the paper.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Byrski, W.: Obserwacja i sterowanie w systemach dynamicznych. Uczelniane Wydawnictwo Naukowo-Dydaktyczne AGH im. S. Staszica, Kraków (2007)
Byrski, W., Drapałla, M., Byrski, J.: 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. Int. J. Appl. Math. Comput. Sci. 29(4), 739–757 (2019)
Byrski, W., Drapała, M., Byrski, J.: New on-line algorithms for modelling, identification and simulation of dynamic systems using modulating functions and non-asymptotic state estimators: case study for a chosen physical process. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds.) ICCS 2021. LNCS, vol. 12745, pp. 284–297. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-77970-2_22
Byrski, W., Fuksa, S.: Optimal identification of continuous systems in L2 space by the use of compact support filter. Int. J. Model. Simul. 15(4), 125–131 (1995)
Drapała, M., Byrski, W.: Continuous-time model predictive control with disturbances compensation for a glass forehearth. In: 2021 25th International Conference on Methods and Models in Automation and Robotics (MMAR), pp. 366–371, 23–26 August 2021
Garnier, H., Gilson, M., Young, P., Huselstein, E.: An optimal IV technique for identifying continuous-time transfer function model of multiple input systems. Control. Eng. Pract. 15(4), 471–486 (2007)
Huisman, L.: Control of glass melting processes based on reduced CFD models. Ph.D. thesis, Technische Universiteit Eindhoven (2005)
Huisman, L., Weiland, S.: Identification and model predictive control of an industrial glass-feeder. IFAC Proc. Vol. 36(16), 1645–1649 (2003)
Malchow, F., Sawodny, O.: Model based feedforward control of an industrial glass feeder. Control. Eng. Pract. 20(1), 62–68 (2012)
Morari, M., Jay, H.L.: Model predictive control: past, present and future. Comput. Chem. Eng. 23(4), 667–682 (1999)
Shinbrot, M.: On the analysis of linear and nonlinear systems. Trans. Am. Soc. Mech. Eng. J. Basic Eng. 79, 547–551 (1957)
Tatjewski, P.: Advanced Control of Industrial Processes: Structures and Algorithms. Advances in Industrial Control, Springer, London (2007). https://doi.org/10.1007/978-1-84628-635-3
Young, P.C.: Optimal IV identification and estimation of continuous-time TF models. IFAC Proc. Vol. 35(1), 109–114 (2002)
Acknowledgements
This work was supported by the scientific research funds from the Polish Ministry of Education and Science and AGH UST Agreement no. 16.16.120.773 and was also conducted within the research of EC Grant H2020-MSCARISE-2018/824046.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Byrski, W., Drapała, M. (2023). A New Version of the On-Line Adaptive Non-standard Identification Procedure for Continuous-Time MISO Physical Processes. In: Kowalczuk, Z. (eds) Intelligent and Safe Computer Systems in Control and Diagnostics. DPS 2022. Lecture Notes in Networks and Systems, vol 545. Springer, Cham. https://doi.org/10.1007/978-3-031-16159-9_34
Download citation
DOI: https://doi.org/10.1007/978-3-031-16159-9_34
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-16158-2
Online ISBN: 978-3-031-16159-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)