“My Way in Cybernetics - For 50 Years”
Authors: Steinar Sælid,Affiliation: Steinar Sælid AS
Reference: 2023, Vol 44, No 4, pp. 155-173.
Keywords: Engineering cybernetics history, dynamic positioning, model based estimation and control, ocean modelling for estimation, applied control theory
Abstract: Increased application of engineering cybernetics- and control engineering have been considerable since the late 1960s. The driving forces have been many, such as improvements/pioneering in defense and space technology, maritime- and oil production technology, robotics and industrial control, enabled by a huge increase in available computing power. I have been involved in this development for the last 50 years. This paper sums up my work within areas such as mathematical modelling for control and estimation, Kalman filtering, and the development of software, simulators and applications for such purposes. During these years I worked, as examples, within the fields of ocean modelling for real-time estimation, oil production, dynamic positioning and industrial control in the fields of fertilizers, and aluminum production. The stories of starting up the company Prediktor and the following development of Manufacturing Execution Systems (MES systems) and my engagement in the use of optical NIR based technology for industrial control in various industries are told. My hope is that the story might be of interest to younger engineers today to understand the development in this engineering cybernetics field for 50 years as exemplified by my career.
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DOI: 10.4173/mic.2023.4.2References:
[1] Berntsen, H., Kowalik, Z., Saelid, S., and Sorli, K. (1981). Efficient numerical simulation of ocean hydrodynamics by a splitting procedure, Modeling, Identification and Control. doi:10.4173/mic.1981.4.1
[2] Bjornstad, S. (2009). Shipshaped: Kongsberg industry and innovations in deep-water technology, 1975-2007, Ph.D. thesis, BI Norwegian School of Management.
[3] Grieves, M. and Vickers, J. (2017). Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems, In Transdisciplinary Perspectives on Complex Systems. Springer, Cham, pages 85--113. doi:10.1007/978-3-319-38756-7_4
[4] Kristoffersen, K. and Saelid, S. (1980). Computer aided design of suboptimal test signals for system identification, In Computer Aided Design of Control Systems. Pergamon, pages 119--125. doi:10.1016/B978-0-08-024488-4.50023-1
[5] McCulloch, W. and Pitts, W. (1943). A logical calculus of the ideas immanent in nervous activity, The Bulletin of Mathematical Biophysics. 5(4):115--133. doi:10.1007/BF02478259
[6] Mjaavatten, A., Aasheim, R., Saelid, S., and Groenning, O. (2008). A model for gas coning and rate-dependent gas/oil ratio in an oil-rim reservoir, SPE Reservoir Evaluation & Engineering. 11(05):842--847.
[7] Moor, J. (2006). The Dartmouth College artificial intelligence conference: The next fifty years, AI Magazine. 27(4):87--87.
[8] Morud, J. and Skogestad, S. (1998). Analysis of instability in an industrial ammonia reactor, AIChE Journal. 44(4):888--895. doi:10.1002/aic.690440414
[9] Rahmanpour, P., Saelid, S., and Hovd, M. (2017). Run-to-run control of the czochralski process, Computers & Chemical Engineering. 104:353--365. http://hdl.handle.net/11250/2475863.
[10] Saelid, S. (1976). Modelling, estimation, and control of a rotary cement kiln, Ph.D. thesis, Norges Tekniske Hogskole (NTH), 1976.
[11] Saelid, S. (1976). State and parameter estimation in a rotary cement kiln, In In IV IFAC Symp. on Ident. and Syst. Par. Est. pages 372--387, 1976.
[12] Saelid, S. (1978). Observability theorems for some linear hyperbolic systems, Automatica. 14(5):499--503. doi:10.1016/0005-1098(78)90009-2
[13] Saelid, S. (1985). Docking control of the flexible riser end in an offshore loading system, Modeling, Identification and Control, 1985. 2(2):75. doi:10.4173/mic.1985.2.2
[14] Saelid, S. (1985). Interactive modeling and simulation using distributed computers and graphical aids, Modeling, Identification and Control, 1985. 6(4):257. doi:10.4173/mic.1985.4.6
[15] Saelid, S. (2019). Mathematical Modeling for Estimation and Control, Amazon Kindle.
[16] Saelid, S. and Foss, B. (1983). Adaptive controllers with a vector variable forgetting factor, In The 22nd IEEE Conference on Decision and Control. IEEE, pages 1488--1494. doi:10.1109/CDC.1983.269785
[17] Saelid, S. and Jenssen, N. (1983). Adaptive ship autopilot with wave filter, Modeling, Identification and Control. 4(1):33--45. doi:10.4173/mic.1983.4.1
[18] Saelid, S., Jenssen, N., Lindstad, T., and Kolbeinsen, L. (1979). Modelling, identification and control of a fluidized bed reactor, In IFAC Proceedings Volumes, 12(8). pages 907--916. doi:10.1016/S1474-6670(17)65508-3
[19] Saelid, S., Svanes, T., Onshus, T., and Jenssen, N. (1984). Design considerations, analysis and practical experience with an adaptive ship's autopilot, IFAC Proceedings Volumes. 17(2):2895--2900. doi:10.1016/S1474-6670(17)61422-8
[20] Solheim, O. and Saelid, S. (1971). Eigenvalue sensitivity in optimal feedback control systems, In 2nd IF4C Symposium on Multivariable technical control systems, Dusseldorf. 1971.
[21] Staal, O., Fougner, A., Saelid, S., and Stavdahl, O. (2019). Glucose-insulin metabolism model reduction and parameter selection using sensitivity analysis, In 2019 American Control Conference (ACC). IEEE, pages 4104--4111, 2019. doi:10.23919/ACC.2019.8814949
[22] Staal, O., Saelid, S., Fougner, A., and Stavdahl, O. (2018). Kalman smoothing for objective and automatic preprocessing of glucose data, IEEE journal of biomedical and health informatics. 23(1):218--226. doi:10.1109/JBHI.2018.2811706
[23] Staal, O., Saelid, S., Fougner, A., and Stavdahl, O. (2019). Meal estimation from continuous glucose monitor data using kalman filtering and hypothesis testing, In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, pages 5654--5661, 2019. doi:10.1109/CDC40024.2019.9028912
[24] Teknisk Ukeblad. (2013). S95: Integrasjon av informasjonssystemer, https://www.tu.no/artikler/s95-integrasjon-av-informasjonssystemer/218457, 2013.
[25] Wassmann, P., Reigstad, M., Haug, T., Rudels, B., Carroll, M., Hop, H., Gabrielsen, G., Falk-Petersen, S., Denisenko, S., Arashkevich, E., Slagstad, D., and Pavlova, O. (2006). Food webs and carbon flux in the barents sea, Progress in Oceanography. 71(2-4):232--287. doi:10.1016/j.pocean.2006.10.003
[26] Wiener, N. (2019). Cybernetics or Control and Communication in the Animal and the Machine, MIT Press (First edition 1961).
[27] Wikipedia. (2023). Manufacturing execution system, https://en.wikipedia.org/wiki/Manufacturing_execution_system, 2023. Accessed on 22.11.2023.
BibTeX:
@article{MIC-2023-4-2,
title={{My Way in Cybernetics - For 50 Years}},
author={Sælid, Steinar},
journal={Modeling, Identification and Control},
volume={44},
number={4},
pages={155--173},
year={2023},
doi={10.4173/mic.2023.4.2},
publisher={Norwegian Society of Automatic Control}
};