RFID Technology for Adaptation of Complex Systems Scheduling and Execution Control Models
In this paper, we investigate the issues of establishing adaptive feedbacks between complex systems (CSs) scheduling and execution from the perspectives of modern control theory. In using optimum control for the scheduling stage, feedback adaptive control for the execution stage, and attainable sets for the analysis of the achievement of the planned performance in a real execution environment, we provide a mathematically unified framework for CSs scheduling and execution control. The proposed framework makes it possible to analyze the correspondence of RFID (Radio Frequency Identification) functionalities and costs to the actual needs of execution control and support problem-oriented CSs adaptation for the achievement of the desired performance. The developed framework can be applied as an analysis tool for the decision support regarding the designing and applying RFID infrastructures in supply chains.
KeywordsComplex systems Scheduling and planning RFID technologies Integrated modeling Multi-agents modeling
The research is supported by Russian Science Foundation (Project No. 16-19-00199).
- 1.Ohtilev, M.Yu., Sokolov, B.V., Yusupov, R.M.: Intellectual Technologies for Monitoring and Control of Structure-Dynamics of Complex Technical Objects, p. 410. Nauka, Moscow (2006) (in Russian)Google Scholar
- 2.Zaychik, E., Sokolov, B., Verzilin, D.: Integrated modeling of structure-dynamics control in complex technical systems. In: 19th European Conference on Modeling and Simulation ESMS 2005, “Simulation in Wider Europe”, 1–4 June 2005, pp. 341–346. Riga Technical University, Riga, Latvia (2005)Google Scholar
- 3.Ivanov, D., Sokolov, B., Arkhipov, A.: Stability analysis in the framework of decision making under risk and uncertainty. In: Camarinha-Matos, L.M., Afsarmanesh, H., Ollus, M. (eds.) Network—Centric Collaboration and Supporting Frameworks, IFIP TC5WG 5.5 Seventh IFIP Working Conference on Virtual Enterprises, 25–27 Sept 2006, pp. 211–218. Springer, Helsinki, Finland (2006)Google Scholar
- 4.Skurihin, V.I., Zabrodsky, V.A., Kopeychenko, Yu.V.: Adaptive Control Systems In Machine-Building Industry. Mashinostroenie (1989) (in Russian)Google Scholar
- 5.Rastrigin, L.A.: Modern Principles of Control for Complicated Objects. Sovetscoe Radio (1980) (in Russian)Google Scholar
- 6.Bellmann, R.: Adaptive Control Processes: A Guided Tour. Princeton University Press, Princeton, New Jersey (1972)Google Scholar
- 7.Rastrigin L.A.: Adaptation of complex systems. Zinatne, Riga (1981) (in Russian)Google Scholar
- 9.Moiseev, N.N.: Element of the Optimal Systems Theory. Nauka (1974) (in Russian)Google Scholar
- 11.Zypkin, Ya.Z.: Adaptation and Teachning in Automatic Systems. Nauka (1969) (in Russian)Google Scholar
- 12.Bryson, A.E., Ho, Yo-Chi: Applied Optimal Control: Optimization Estimation and Control. Waltham, Massachusetts (1969)Google Scholar
- 17.Rabelo, R.J., Klen, A.A.P., Klen, E.R.: Multi-agent system for smart coordination of dynamic supply chains. In: Proceedings of the 3rd International Conference on Virtual Enterprises, PRO-VE’2002. pp. 379–387 (2002)Google Scholar
- 21.Huber, S., Michael, K., McCathie, L.: Barriers to RFID adoption in the supply chain Barriers to RFID adoption in the supply chain. In: IEEE RFID Eurasia, pp. 1–6. 5–6 September, Istanbul, Turkey (2007)Google Scholar
- 27.Dashevsky, V., Sokolov, B. (2010). New concept of RFID reader networks structure: hardware and software architecture. In: Proceedings of International Conference on Ultra Modern Telecommunications ICUMT-2009, Saint-Petersburg, RussiaGoogle Scholar
- 28.Bhardwaj, A., Singh, V.K., Kumar, P.: Multi-agent based train passing in railway system with minimum system delay. In: 2014 IEEE International Advance Computing Conference (IACC) (2014)Google Scholar
- 29.Niazi, M., Hussain, A.: Agent-based computing from multi-agent systems to agent-based Models: a visual survey. Scientometrics (2011)Google Scholar
- 30.Müller, J.P.: Des systèmes autonomes aux systèmes multi-agents: Interaction, émergence et systems complexes. Mémoire d’habilitation (2002)Google Scholar
- 32.Salamon, T.: Design of Agent-Based Models. Repin: Bruckner Publishing. p. 22 (2011). ISBN 978-80-904661-1-1Google Scholar
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