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General Information
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
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).

[PDF]

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.

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