@inproceedings{7ed015a9c6e34e0f944ddb4ea8271f86,
title = "Adaptive robust control based on T-S fuzzy-neural systems for a hypersonic vehicle",
abstract = "This paper proposes a on-line modeling and control approach through Takagi-Sugeno (T-S) fuzzy-neural model for a class of generalized multiple input multiple output (MIMO) nonlinear dynamic systems with external disturbances. Nonlinear systems are exactly formed a linearized system via the mean value theroem, and then the T-S fuzzy-neural model can approximate the linearized system. Then on-line identificatoin algorithm and an adaptive scheme are used on tracking controller design. A hypersonic vehicle is modeled and attitude controller is designed using the proposed method. Simulation results on guidance, navigation and control (GNC) platform show a satisfactory performance for the attitude tracking.",
keywords = "Hypersonic vehicle, MIMO nonlinear systems, T-S fuzzy model, adaptive control, robust control",
author = "Qu Xin and Ren Zhang",
year = "2011",
doi = "10.1109/ICECENG.2011.6057682",
language = "英语",
isbn = "9781424481637",
series = "2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings",
pages = "535--538",
booktitle = "2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings",
note = "2nd Annual Conference on Electrical and Control Engineering, ICECE 2011 ; Conference date: 16-09-2011 Through 18-09-2011",
}