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Modeling and analysis of human control actions using fuzzy interactive information systems

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EN
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EN
This paper focuses on the problem of modeling and analyzing the actions of human operators who perform demanding tasks such as real-time control of a complex dynamic plant. To this end, an approach that bases on the idea of interactive fuzzy information systems is proposed. In particular, we discuss the problem of selecting and generating perception and action attributes to describe the aircraft control tasks realized by a skilled pilot. A method consisting of several stages is proposed for modeling pilot-airplane interactions. The initial information system with sensory attributes is replaced with more complex attributes at subsequent stages. To determine the decision rules of the pilot, we apply flow graphs that are suitable for representing fuzzy interactive information systems and for evaluating properties and quality of the human operator’s decision model.
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  • Rzeszów University of Technology, Rzeszów, Poland
Bibliografia
  • [1] D. T. McRuer and E. S. Krendel, Mathematical Models of Human Pilot Behavior. AGARD AG-188, 1974.
  • [2] R. Hess and A. Marchesi, “Analytical assessment of flight simulator fi-delity using pilot models,” Journal of Guidance, Control and Dynamics, vol. 32, pp. 760-770, 2009.
  • [3] R. Hess, “Structural model of the adaptive human pilot,” Journal of Guidance, Control, and Dynamics, vol. 3, no. 5, pp. 416-423, 1979.
  • [4] M. Jirgl and R. Jalovecky, “Models of pilot behavior and their use to evaluate the state of pilot training,” Journal of Electrical Engineering, vol. 67, no. 4, pp. 267-272, 2016.
  • [5] M. Jirgl, M. Havlikova, and Z. Bradac, “The dynamic pilot behavioral model,” Procedia Engineering, vol. 100, pp. 1192-1197, 2015.
  • [6] A. V. Efremov, M. S. Tjaglik, U. V. Tiumentzev, and T. Wenqian, “Pilot behavior modeling and its application to manual control tasks,” IFAC - PapersOnLine, vol. 49-32, pp. 159-164, 2016.
  • [7] H. Wu, F. Kang, W. Huang, and Y. Lu, “Modeling and simulation of pilot behavior interfaced with avionics system,” in ICSC 2012, Part II, CCIS 327, T. Xiao, L. Zhang, and S. Ma, Eds. Berlin Heidelberg: Springer-Verlag, 2012, pp. 390-398.
  • [8] M. Gestwa, “Using fuzzy control for modeling the control behaviour of a human pilot,” in Fuzzy Controllers, Theory and Applications, L. Grigorie, Ed. InTech, 2011, pp. 297-326.
  • [9] A. Skowron and P. Wasilewski, “Information systems in modeling interactive computations on granules,” Theoretical Computer Science, vol. 412, pp. 5939-5959, 2011.
  • [10] A. Skowron and P. Wasilewski, “Interactive information systems: Toward perception based computing,” Theoretical Computer Science, vol. 454, pp. 240-260, 2012.
  • [11] Z. Pawlak, Rough Sets: Theoretical Aspects of Reasoning about Data. Boston Dordrecht London: Kluwer Academic Publishers, 1991.
  • [12] A. Skowron, A. Jankowski, and S. Dutta, “Interactive granular comput-ing,” Granular computing, vol. 1, pp. 95-113, 2016.
  • [13] A. Jankowski, Interactive Granular Computations in Networks and Systems Engineering: A Practical Perspective, ser. Lecture Notes in Networks and Systems. Berlin Heidelberg: Springer, 2017.
  • [14] A. Skowron and S. Dutta, “From information systems to interactive in-formation systems,” in Thriving Rough Sets: 10th Anniversary-Honoring Professor Zdzisław Pawlak’s Life and Legacy 35 Years of Rough Sets, ser. Studies in Computational Intelligence, G. Wang, A. Skowron, Y. Yao, D. Ślęzak, and L. Polkowski, Eds., vol. 708. Cham: Springer, 2017, pp. 207-223.
  • [15] S. Dutta and A. Skowron, “Interactive granular computing connecting abstract and physical worlds: An example,” in Proceedings of the 29th International Workshop on Concurrency, Specification and Program-ming, Berlin, 2021, pp. 46-59.
  • [16] S. Dutta and A. Skowron, “Toward a computing model dealing with complex phenomena: Interactive granular computing,” in Proceedings of the Computational Collective Intelligence - 13th International Con-ference, Rhodes, 2021, pp. 199-214.
  • [17] A. Mieszkowicz-Rolka and L. Rolka, “On representation and analysis of crisp and fuzzy information systems,” in Transactions on Rough Sets VI, ser. Lecture Notes in Computer Science (Journal Subline), J. F. Peters et al., Eds., vol. 4374. Berlin Heidelberg: Springer-Verlag, 2007, pp. 191-210.
  • [18] A. Mieszkowicz-Rolka and L. Rolka, “Fuzzy flow graphs in analysis of the pilot’s control actions,” in Information Systems Architecture and Technology, ser. Library of Informatics of University Level Schools, J. Świątek et al., Eds. Wrocław, 2013, pp. 165-174.
  • [19] A. Mieszkowicz-Rolka and L. Rolka, “Flow graphs and decision tables with fuzzy attributes,” in Artificial Intelligence and Soft Computing — ICAISC 2006, ser. Lecture Notes in Artificial Intelligence, L. Rutkowski et al., Eds., vol. 4029. Berlin Heidelberg: Springer-Verlag, 2006, pp. 268-277.
  • [20] A. Mieszkowicz-Rolka and L. Rolka, “Variable precision fuzzy rough sets model in the analysis of process data,” in Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, ser. Lecture Notes in Artificial Intelligence, D. Ślęzak et al., Eds., vol. 3641. Berlin Heidelberg: Springer-Verlag, 2005, pp. 354-363.
  • [21] A. Mieszkowicz-Rolka and L. Rolka, “Multi-criteria decision-making with linguistic labels,” in Proceedings of the 17th Conference on Com-puter Science and Intelligence Systems, ser. Annals of Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, and D. Ślęzak, Eds., vol. 30. IEEE, 2022, pp. 263-267. [Online]. Available: http://dx.doi.org/10.15439/2022F218
  • [22] Z. Pawlak, “Decision algorithms, Bayes’ theorem and flow graphs,” in Advances in Soft Computing, L. Rutkowski and J. Kacprzyk, Eds. Heidelberg: Physica-Verlag, 2003, pp. 18-24.
  • [23] Z. Pawlak, “Flow graphs and data mining,” in Transactions on Rough Sets III, ser. Lecture Notes in Computer Science (Journal Subline), J. F. Peters et al., Eds., vol. 3400. Berlin Heidelberg: Springer-Verlag, 2005, pp. 1-36.
  • [24] Z. Pawlak, “Rough sets and flow graphs,” in Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, ser. Lecture Notes in Artificial Intelligence, D. ´Sl˛ezak et al., Eds., vol. 3641. Berlin Heidelberg: Springer-Verlag, 2005, pp. 1-11.
Typ dokumentu
Bibliografia
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