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2017 | 24 | 3 |
Tytuł artykułu

Comparison of fuzzy system with neural aggregation FSNA with classical TSK fuzzy system in anti-collision problem of USV

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents the research whose the main goal was to compare a new Fuzzy System with Neural Aggregation of fuzzy rules FSNA with a classical Takagi-Sugeno-Kanga TSK fuzzy system in an anti-collision problem of Unmanned Surface Vehicle USV. Both systems the FSNA and the TSK were learned by means of Cooperative Co-evolutionary Genetic Algorithm with Indirect Neural Encoding CCGA-INE. The paper includes an introduction to the subject, a description of the new FSNA and the tuning method CCGA-INE, and at the end, numerical research results with a summary. The research includes comparison of the FSNA with the classical TSK system in the anti-collision problem of the USV
Słowa kluczowe
EN
Wydawca
-
Rocznik
Tom
24
Numer
3
Opis fizyczny
p.3-14,fig.,ref.
Twórcy
autor
  • Polish Naval Academy, Smidowicza 69, 81-127 Gdynia, Poland
Bibliografia
  • 1. D. Driankov, H. Hellendoorn, M. Reinfrank, An Introduction to Fuzzy Control, Springer-Verlag, 1996.
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  • 9. K. Naus, M. Wąż, A simplified navigational chart pyramid dedicated to an autonomous navigational system, Polish Hyperbaric Research, Vol. 3(40), pp. 99-118, 2012.
  • 10. S. Osowski, Neural networks for data processing, in polish, Publishing House of Technology University in Warsaw, 2006.
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  • 13. T. Praczyk, P. Szymak, “Decision System for a Team of Autonomous Underwater Vehicles – Preliminary Report”, Neurocomputing, Vol. 74 (17), pp. 3323-3334, 2011.
  • 14. T. Praczyk, P. Szymak, “Using Genetic Algorithms to Fix a Route for an Unmanned Surface Vehicle”, in Proceedings of the 17th International Conference on Methods and Models in Automation and Robotics, pp. 487-492, 2012.
  • 15. P. Szymak, T. Praczyk, “Using Neural-Evolutionary-Fuzzy Algorithm for Anti-collision System of Unmanned Surface Vehicle”, in Proceedings of the 17th International Conference on Methods and Models in Automation and Robotics, pp. 286-290, 2012.
  • 16. P. Szymak, “Course Control of Unmanned Surface Vehicle”, Solid State Phenomena, Vol. 196, pp. 117-123, 2013.
  • 17. T. Takagi, M. Sugeno, “Fuzzy Identification of Systems and its Application to Modelling and Control”, IEEE Transactions on Systems, Man and Cybernetics, vol. 15, pp. 116-132, 1985.
  • 18. J. Vieira, F.M. Dias, A. Mota, Neuro-Fuzzy Systems: A Survey, WSEAS Transactions on Systems, 3(2), 2004.
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  • 20. Y. Zhuo, “An intelligent decision support system to ship anti-collision in multi-ship encounter”, in Proceedings of the Intelligent Control and Automation 2008, pp. 1066–1071, 2008.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.agro-c7d8a589-866e-4bb1-9d3a-8cfa3d52f5c4
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