Author:
Chang Shunzhang,Liu Shiyue,Chen Jiabin
Abstract
Abstract
In this paper, an attitude control method combining radial basis (RBF) neural network with integral sliding mode control is proposed for the re-entry stage of hypersonic vehicle with uncertain aerodynamic parameters and atmospheric density. Firstly, the Time-scale separation model of nonlinear equations for aircraft is established. Meanwhile, the feedback linearization method is used to linearize the time scale separation model. For fast and slow control subloops, a global sliding mode variable structure control was designed, and the stability of the closed-loop system was verified by Lyapunov theory. Finally, RBF neural network online regulation law is designed to adjust the controller parameters online to reduce chattering. The simulation results show that the controller can maintain good dynamic characteristics even when the aerodynamic data are greatly deviated.
Subject
General Physics and Astronomy
Reference9 articles.
1. J. Study on several scientific problems of nearspace hypersonic vehicle control;Chang-yin;Acta Automatica Sinica,2013
2. J. Exponential time-varing sliding mode control design for a hypersonic cruise air vehicle;Zhu;J of Astronautics,2011
3. J. Study on multidisciplinary dynamics modeling of inspiratory hypersonic vehicle;Ru-hao;Acta Aeronautics et Astronautics Sinica,2015
4. J. Flight control for an aerospace vehicle’s reentry attitude based on thrust of reaction jets;Chengshan;Journal of Aerospace Power,2008
5. J. Quasi-continuous high-order sliding mode controller design for reusable launch vehicles in reentry phase;Tian;Aerospace Science and Technology,2013
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