DocumentCode :
164166
Title :
Neural dynamic surface hypersonic flight control using minimal-learning-parameter technique
Author :
Bin Xu ; Lin Yu ; Shixing Wang ; Xiaoqing Feng
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
fYear :
2014
fDate :
27-30 May 2014
Firstpage :
960
Lastpage :
966
Abstract :
This paper presents dynamic surface control for longitudinal dynamics of a generic hypersonic flight vehicle in presence of unknown dynamics. For the attitude subsystem, the minimal-learning-parameter technique is combined with dynamic surface design. The uniform ultimate boundedness stability is guaranteed via Small-gain Theorem. The singularity problem is removed and the simpler adaptive algorithm is easy to implement since the online updating computation burden is greatly reduced. Simulation result shows the feasibility of the proposed method.
Keywords :
adaptive control; aircraft control; attitude control; learning systems; neurocontrollers; stability; adaptive algorithm; attitude subsystem; dynamic surface design; generic hypersonic flight vehicle; longitudinal dynamics; minimal-learning-parameter technique; neural dynamic surface hypersonic flight control; online updating computation; singularity problem; small-gain theorem; uniform ultimate boundedness stability guarantee; unknown dynamics; Aerodynamics; Artificial neural networks; Control systems; Educational institutions; Simulation; Vehicle dynamics; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Unmanned Aircraft Systems (ICUAS), 2014 International Conference on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/ICUAS.2014.6842346
Filename :
6842346
Link To Document :
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