Home > Archive > 2015 > Volume 5 Number 4 (Aug. 2015) >
IJMLC 2015 Vol. 5(4): 301-306 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2015.V5.524

Learning Control Law of Mode Switching for Hypersonic Morphing Aircraft Based on Type-2 TSK Fuzzy Neural Network

Xin Jiao and Ju Jiang

Abstract—A novel learning method of control law of mode switching for hypersonic morphing aircraft, based on type-2 Takagi- Sugeno -Kang (TSK) fuzzy neural network, is proposed in this paper. The purpose of this method is to learn the control law of mode switching from a group of training data, in order to steadily and smoothly switch the winglets from retracting to stretching mode. In this method, taking into consideration the characteristics of type-2 fuzzy, we utilize an interval type-2 TSK fuzzy approach, the rules of which are learned from training data by back- propagation algorithm. Simulation results indicate that the proposed learning method of switching control law, based on type-2 TSK fuzzy neural network, can steadily and smoothly switch the winglets from retracting to stretching mode, providing a novel method for obtaining an excellent switching control law in situations with a group of training data.

Index Terms—Control law of mode switching, learning rules, interval type-2 TSK fuzzy, back-propagation algorithm, hypersonic morphing aircraft.

The authors are with the Automation Department, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016 China (e-mail: jiaoxin_mengqu@163.com, jiangju@nuaa.edu.cn).

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Cite: Xin Jiao and Ju Jiang, "Learning Control Law of Mode Switching for Hypersonic Morphing Aircraft Based on Type-2 TSK Fuzzy Neural Network," International Journal of Machine Learning and Computing vol. 5, no. 4, pp. 301-306, 2015.

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net


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