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).
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.