“A metamorphic controller for plant control system design”
Authors: Tomasz Klopot, Piotr Skupin, Dariusz Choinski, Rafal Cupek and Marcin Fojcik,Affiliation: Silesian University of Technology and Sogn and Fjordane University College
Reference: 2016, Vol 37, No 3, pp. 159-169.
Keywords: model-based design, parallel design, programmable logic controller, control system design, simulation
Abstract: One of the major problems in the design of industrial control systems is the selection and parameterization of the control algorithm. In practice, the most common solution is the PI (proportional-integral) controller, which is simple to implement, but is not always the best control strategy. The use of more advanced controllers may result in a better efficiency of the control system. However, the implementation of advanced control algorithms is more time-consuming and requires specialized knowledge from control engineers. To overcome these problems and to support control engineers at the controller design stage, the paper describes a tool, i.e., a metamorphic controller with extended functionality, for selection and implementation of the most suitable control algorithm. In comparison to existing solutions, the main advantage of the metamorphic controller is its possibility of changing the control algorithm. In turn, the candidate algorithms can be tested through simulations and the total time needed to perform all simulations can be less than a few minutes, which is less than or comparable to the design time in the concurrent design approach. Moreover, the use of well-known tuning procedures, makes the system easy to understand and operate even by inexperienced control engineers. The application was implemented in the real industrial programmable logic controller (PLC) and tested with linear and nonlinear virtual plants. The obtained simulation results confirm that the change of the control algorithm allows the control objectives to be achieved at lower costs and in less time.
PDF (1526 Kb) DOI: 10.4173/mic.2016.3.2
DOI forward links to this article:
[1] Piotr Laszczyk, Malgorzata Niedzwiedz, Piotr Skupin and Mieczyslaw Metzger (2017), doi:10.1109/PC.2017.7976218 |
[2] Michal Fratczak, Pawel Nowak and Piotr Laszczyk (2017), doi:10.1109/MMAR.2017.8046843 |
[3] Edi Dwi Nugroho, Aji Gautama Putrada and Andrian Rakhmatsyah (2021), doi:10.1109/ISESD53023.2021.9501402 |
[4] Patryk Grelewicz, Pawel Nowak, Michal Fratczak and Tomasz Klopot (2018), doi:10.1109/MMAR.2018.8485990 |
[1] Abdullah, R., Hussain, A., Warwick, K., and Zayed, A. (2008). Abdullah, R, , Hussain, A., Warwick, K., and Zayed, A. Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning. Neurocomputing. 71(13):2727--2741. doi:10.1016/j.neucom.2007.05.016
[2] Balasubramanian, S., Brennan, R.W., and Norrie, D.H. (2001). Balasubramanian, S, , Brennan, R.W., and Norrie, D.H. An architecture for metamorphic control of holonic manufacturing systems. Computers in Industry. 46(1):13--31. doi:10.1016/S0166-3615(01)00101-4
[3] Barth, M. and Fay, A. (2013). Barth, M, and Fay, A. Automated generation of simulation models for control code tests. Control Engineering Practice. 21(2):218--230. doi:10.1016/j.conengprac.2012.09.022
[4] Bradu, B., Gayet, P., and Niculescu, S.-I. (2009). Bradu, B, , Gayet, P., and Niculescu, S.-I. A process and control simulator for large scale cryogenic plants. Control Engineering Practice. 17(12):1388--1397. doi:10.1016/j.conengprac.2009.07.003
[5] Budzan, S. and Wyzgolik, R. (2014). Budzan, S, and Wyzgolik, R. Noise reduction in thermal images. In Computer Vision and Graphics, pages 116--123. Springer, 2014. doi:0.1007/978.3.319.11331.9.15
[6] Czeczot, J. (2006). Czeczot, J, Balance-based adaptive control of a neutralisation process. International Journal of control. 79(12):1581--1600. doi:10.1080/00207170600865358
[7] Davendra, D., Zelinka, I., and Senkerik, R. (2010). Davendra, D, , Zelinka, I., and Senkerik, R. Chaos driven evolutionary algorithms for the task of pid control. Computers & Mathematics with Applications. 60(4):1088--1104. doi:10.1016/j.camwa.2010.03.066
[8] Eriksson, P.-G. and Isaksson, A.J. (1994). Eriksson, P, -G. and Isaksson, A.J. Some aspects of control loop performance monitoring. In Control Applications., Proceedings of the Third IEEE Conference on. IEEE, pages 1029--1034. doi:10.1109/CCA.1994.381372
[9] Fratczak, M., Klopot, T., Czeczot, J., and Bregulla, M. (2013). Fratczak, M, , Klopot, T., Czeczot, J., and Bregulla, M. Representative vector method for modeling of energy consumption for the assembly line. In Methods and Models in Automation and Robotics (MMAR), 2013 18th International Conference on. IEEE, pages 420--425. doi:10.1109/MMAR.2013.6669945
[10] Geist, S., Kleinert, T., Klauer, C., Wigger, M., Milbredt, J., Nejad, B.M., Le, T., and Hoeser, S. (2013). Geist, S, , Kleinert, T., Klauer, C., Wigger, M., Milbredt, J., Nejad, B.M., Le, T., and Hoeser, S. Dynamic simulation of an integrated thermal separation unit considering practically relevant conditions and limitations. Journal of Process Control. 23(7):980--989. doi:10.1016/j.jprocont.2013.05.001
[11] Gerlach, I., Hass, V.C., Bruning, S., and Mandenius, C.-F. (2013). Gerlach, I, , Hass, V.C., Bruning, S., and Mandenius, C.-F. Virtual bioreactor cultivation for operator training and simulation: application to ethanol and protein production. Journal of Chemical Technology and Biotechnology. 88(12):2159--2168. doi:10.1002/jctb.4079
[12] Groover, M.P. (2007). Groover, M, P. Automation, production systems, and computer-integrated manufacturing. Prentice Hall Press. doi:10.1108/aa.2002.22.3.298.2
[13] Gyoengy, I. and Clarke, D. (2006). Gyoengy, I, and Clarke, D. On the automatic tuning and adaptation of pid controllers. Control Engineering Practice. 14(2):149--163. doi:10.1016/j.conengprac.2005.01.007
[14] Hagglund, T. (1995). Hagglund, T, A control-loop performance monitor. Control Engineering Practice. 3(11):1543--1551. doi:10.1016/0967-0661(95)00164-P
[15] Huang, B., Shah, S., and Kwok, E. (1997). Huang, B, , Shah, S., and Kwok, E. Good, bad or optimal? performance assessment of multivariable processes. Automatica. 33(6):1175--1183. doi:10.1016/S0005-1098(97)00017-4
[16] Kasprzyczak, L. and Macha, E. (2008). Kasprzyczak, L, and Macha, E. Selection of settings of the pid controller by automatic tuning at the control system of the hydraulic fatigue stand. Mechanical Systems and Signal Processing. 22(6):1274--1288. doi:10.1016/j.ymssp.2007.08.014
[17] Kasprzyczak, L. and Macha, E. (2015). Kasprzyczak, L, and Macha, E. Structures of proportional--integral--derivative regulators for control of stress, strain and energy parameters at the electro-hydraulic fatigue test stand. Journal of Vibration and Control. 21(1):68--80. doi:10.1177/1077546313479635
[18] Kim, J., Kim, I., and Choi, H. (2011). Kim, J, , Kim, I., and Choi, H. 3d virtual knowledge space for collaboration in new product development processes. Concurrent Engineering: R&A. 19(2):101--110. doi:10.1177/1063293X11407937
[19] Ko, M., Ahn, E., and Park, S.C. (2013). Ko, M, , Ahn, E., and Park, S.C. A concurrent design methodology of a production system for virtual commissioning. Concurrent Engineering, 2013. page 1063293X13476070. doi:10.1177/1063293X13476070
[20] Ko, M. and Park, S.C. (2014). Ko, M, and Park, S.C. Template-based modeling methodology of a virtual plant for virtual commissioning. Concurrent Engineering. 22(3):197--205. doi:10.1177/1063293X14531423
[21] Ko, M., Park, S.C., and Chang, M. (2013). Ko, M, , Park, S.C., and Chang, M. Control level simulation of an automatic storage and retrieval system in the automotive industry. Concurrent Engineering, 2013. 21(1):13--25. doi:10.1177/1063293X12474830
[22] Koo, L.-J., Park, C.M., Lee, C.H., Park, S., and Wang, G.-N. (2011). Koo, L, -J., Park, C.M., Lee, C.H., Park, S., and Wang, G.-N. Simulation framework for the verification of plc programs in automobile industries. International Journal of Production Research. 49(16):4925--4943. doi:10.1080/00207543.2010.492404
[23] Laszczyk, P. (2001). Laszczyk, P, Simulation based evaluation of pi, pfc and gmc control for electric heater. In Proceedings of the 13th SCS European Simulation Symposium on Simulation in Industry. pages 202--205. .
[24] Laszczyk, P. and Czeczot, J. (2012). Laszczyk, P, and Czeczot, J. Nonminimum-phase process control with controllers based on simplified modeling. In Control Applications (CCA), 2012 IEEE International Conference on. IEEE, pages 1652--1657. doi:10.1109/CCA.2012.6402373
[25] Laszczyk, P., Czeczot, J., Czubasiewicz, R., and Stebel, K. (2012). Laszczyk, P, , Czeczot, J., Czubasiewicz, R., and Stebel, K. Practical verification of the control strategies for the counter-current heat exchanger. In Methods and Models in Automation and Robotics (MMAR), 2012 17th International Conference on. IEEE, pages 96--101. doi:10.1109/MMAR.2012.6347904
[26] Laszczyk, P., Klopot, T., and Pyka, D. (2013). Laszczyk, P, , Klopot, T., and Pyka, D. Comparison of dmc and pfc control for heating process. In Methods and Models in Automation and Robotics (MMAR), 2013 18th International Conference on. IEEE, pages 317--322. doi:10.1109/MMAR.2013.6669926
[27] Lee, C.G. and Park, S.C. (2014). Lee, C, G. and Park, S.C. Survey on the virtual commissioning of manufacturing systems. Journal of Computational Design and Engineering. 1(3):213--222. doi:10.7315/JCDE.2014.021
[28] Li, Y., Ang, K.H., etal. (2006). Li, Y, , Ang, K.H., etal. Patents, software, and hardware for pid control: an overview and analysis of the current art. Control Systems, IEEE, 2006. 26(1):42--54. doi:10.1109/MCS.2006.1580153
[29] Li, Y., Ang, K.H., etal. (2006). Li, Y, , Ang, K.H., etal. Pid control system analysis and design. Control Systems, IEEE, 2006. 26(1):32--41. doi:10.1109/MCS.2006.1580152
[30] Paul, A., Akar, M., Safonov, M.G., and Mitra, U. (2005). Paul, A, , Akar, M., Safonov, M.G., and Mitra, U. Adaptive power control for wireless networks using multiple controllers and switching. Neural Networks, IEEE Transactions on. 16(5):1212--1218. doi:10.1109/TNN.2005.853420
[31] Polakow, G. and Metzger, M. (2013). Polakow, G, and Metzger, M. Performance evaluation of the parallel processing producer--distributor--consumer network architecture. Computer Standards & Interfaces. 35(6):596--604. doi:10.1016/j.csi.2013.04.004
[32] Seborg, D.E., Mellichamp, D.A., Edgar, T.F., and DoyleIII, F.J. (2010). Seborg, D, E., Mellichamp, D.A., Edgar, T.F., and DoyleIII, F.J. Process dynamics and control. John Wiley & Sons. .
[33] Stebel, K., Czeczot, J., and Laszczyk, P. (2014). Stebel, K, , Czeczot, J., and Laszczyk, P. General tuning procedure for the nonlinear balance-based adaptive controller. International Journal of Control. 87(1):76--89. doi:10.1080/00207179.2013.822103
[34] Stebel, K. and Metzger, M. (2012). Stebel, K, and Metzger, M. Distributed parameter model for ph process including distributed continuous and discrete reactant feed. Computers & Chemical Engineering. 38:82 -- 93. doi:10.1016/j.compchemeng.2011.11.006
[35] Szczypka, D. (2011). Szczypka, D, Metamorphic control system. Master's thesis, Silesian University of Technology, Gliwice, Poland, 2011. .
[36] Vyatkin, V. (2012). Vyatkin, V, IEC 61499 Function Blocks for Embedded and Distributed Control Systems Design, Second Edition. International Society of Automation. .
[37] Wang, R., Paul, A., Stefanovic, M., and Safonov, M.G. (2007). Wang, R, , Paul, A., Stefanovic, M., and Safonov, M.G. Cost detectability and stability of adaptive control systems. International Journal of Robust and Nonlinear Control. 17(5-6):549--561. doi:10.1002/rnc.1122
[38] Wilson, C. and Callen, C. (2004). Wilson, C, and Callen, C. Close process control translates to quality heat treated parts. Industrial Heating. 71(1):25--28. .
[39] Xu, Y., Brennan, R., Zhang, X., and Norrie, H. (2002). Xu, Y, , Brennan, R., Zhang, X., and Norrie, H. A reconfigurable concurrent function block model and its implementation in real-time java. Integrated Computer--Aided Engineering. 9(3):263--279. .
[40] Yu, C.-C. (2006). Yu, C, -C. Features of proportional-integral-derivative control. Autotuning of PID Controllers: A Relay Feedback Approach, 2006. pages 9--21. doi:10.1007/b137042
BibTeX:
@article{MIC-2016-3-2,
title={{A metamorphic controller for plant control system design}},
author={Klopot, Tomasz and Skupin, Piotr and Choinski, Dariusz and Cupek, Rafal and Fojcik, Marcin},
journal={Modeling, Identification and Control},
volume={37},
number={3},
pages={159--169},
year={2016},
doi={10.4173/mic.2016.3.2},
publisher={Norwegian Society of Automatic Control}
};