Abstract
Physical swarm unit, as an object under digital control is analyzed. It is shown, that Von Neumann digital controller, as a physical device, has new properties in comparison with analogue controllers, namely due to sequentially interpretation of control algorithm there are time delays between quests to sensors and actuators, that cause influence on a swarm unit performance as a whole. Flowchart of digital control system is worked out and closed loops transfer function, which takes into account real properties of Von Neumann digital controller, is obtained. The method of time lags estimation, based on notion the interpretation of arbitrary complexity cyclic algorithm as semi-Markov process, is proposed. Theoretical postulates are confirmed by simulation of two-loop digital control system functioning. Results of simulation emphatically show how data skew and feedback lag affect on swarm unit control dynamics.
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References
Bouallègue, S., Haggège, J., Ayadi, M., Benrejeb, M.: PID-type fuzzy logic controller tuning based on particle swarm optimization. Eng. Appl. Artif. Intell. 25(3), 484–493 (2012). https://doi.org/10.1016/j.engappai.2011.09.018
Reyes-Sierra, M., Coello Coello, C.A.: Multi-objective particle swarm optimizers: a survey of the state-of-the-art. Int. J. Comput. Intell. Res. 2(3), 287–308 (2006). https://doi.org/10.5019/j.ijcir.2006.68
Babishin, V., Taghipour, S.: Optimal maintenance policy for multicomponent systems with periodic and opportunistic inspections and preventive replacements. Appl. Math. Model. 40(23), 10480–10505 (2016). https://doi.org/10.1016/j.apm.2016.07.019
Larkin, E., Antonov, M.: On assessing the temporal characteristics of reaching the milestone by a swarm. In: Tan, Y., Shi, Y., Tuba, M. (eds.) ICSI 2020. LNCS, vol. 12145, pp. 46–55. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-53956-6_5
Landau, I.D., Zito, G.: Digital Control Systems, Design, Identification and Implementation, p. 484. Springer, Heidelberg (2006)
Aström, J., Wittenmark, B.: Computer Controlled Systems: Theory and Design, p. 557. Tsinghua University Press. Prentice Hall (2002)
Fadali, M.S., Visioli, A.: Digital Control Engineering: Analysis and Design, pp. 239–272. Elsevier Inc. (2013)
Larkin, E.V., Ivutin, A.N.: Estimation of latency in embedded real-time systems. In: 3rd Meditteranean Conference on Embedded Computing (MECO-2014), Budva, Montenegro, pp. 236–239 (2014)
Auslander, D.M., Ridgely, J.R., Jones, J.C.: Real-time software for implementation of feedback control. In: Levine, W.S. (ed.) The Control Handbook. Control System Fundamentals, pp. 16-1–16-32. CRC Press. Taylor and Francis Group (2017)
Karnopp, D.C., Margolis, D.L., Rosenberg, R.C.: System Dynamics: Modeling, Simulation and Control of Mechatronic Systems, p. 636. Hoboken, Willey (2012)
Bielecki, T., Jakubowski, J., Niewęgłowski, M.: Conditional Markov chains: properties, construction and structured dependence. Stochast. Process. Appl. 127(4), 1125–1170 (2017). https://doi.org/10.1016/j.spa.2016.07.010
Ching, W.K., Huang, X., Ng, M.K., Siu, T.K.: Markov Chains: Models, Algorithms and Applications. International Series in Operations Research & Management Science, vol. 189, p. 241. Springer, New York (2013)
Howard, R.A.: Dynamic Probabilistic Systems, vol. 1: Markov Models. vol. II: Semi-Markov and Decision Processes. Courier Corporation (2012)
Janssen, J., Manca, R.: Applied Semi-Markov Processes, p. 310. Springer, Heidelberg (2006)
Schiff, J.L.: The Laplace Transform: Theory and Applications, p. 233. Springer, New York (1991)
Li, J., Farquharson, C.G., Hu, X.: Three effective inverse Laplace transform algorithms for computing time -domain electromagnetic responses. Geophysics 81(2), E75–E90 (2015)
Arnold, K.A.: Timing analysis in embedded systems. In: Ganssler, J., Arnold, K., et al. (eds.) Embedded Hardware, pp. 239–272. Elsevier Inc. (2008)
Balsamo, S., Harrison, P., Marin, A.: Methodological construction of product-form stochastic Petri nets for performance evaluation. J. Syst. Softw. 85(7), 1520–1539 (2012). https://doi.org/10.1016/j.jss.2011.11.1042
Larkin, E., Akimenko, T., Privalov, A.: Synchronized swarm operation. In: Tan, Y., Shi, Y., Tuba, M. (eds.) Advances in Swarm Intelligence, ICSI 2020, pp. 15–24. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-53956-6_2
Kobayashi, H., Marl, B.L., Turin, W.: Probability, Random Processes and Statistical Analysis, p. 812. Cambridge University Press (2012)
Pukelsheim, F.: The three sigma rule. Am. Stat. 48(2), 88–91 (1994)
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Larkin, E., Privalov, A., Akimenko, T. (2021). Swarm Unit Digital Control System Simulation. In: Tan, Y., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2021. Lecture Notes in Computer Science(), vol 12689. Springer, Cham. https://doi.org/10.1007/978-3-030-78743-1_1
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DOI: https://doi.org/10.1007/978-3-030-78743-1_1
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