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基于单隐层神经网络的空天飞行器直接自适应轨迹线性化控制
引用本文:朱亮,姜长生,陈海通,方炜.基于单隐层神经网络的空天飞行器直接自适应轨迹线性化控制[J].宇航学报,2006,27(3):338-344,353.
作者姓名:朱亮  姜长生  陈海通  方炜
作者单位:南京航空航天大学自动化学院,南京,210016
基金项目:国家高技术研究发展计划(863计划)
摘    要:基于轨迹线性化方法(TLC)及神经网络技术研究了一种新的直接自适应TCC控制方案。利用单隐层神经网络(SHLNN)对于光滑非线性函数的逼近能力,对消系统中不确定因素的影响,神经网络自适应律采用Lyapunov方法设计,保证了整个系统所有信号有界。最后利用该方案设计了空天飞行器飞行控制系统,并在高超声速飞行条件下进行了仿真验证,仿真结果表明整个控制系统具有很好的性能和鲁棒性。

关 键 词:飞行控制  轨迹线性化控制  神经网络  自适应控制
文章编号:1000-1328(2006)03-0338-07
收稿时间:2005-10-18
修稿时间:2005-10-182006-03-07

Direct Adaptive Trajectory Linearization Control of Aerospace Vehicle Using SHLNN
ZHU Liang,JIANG Chang-sheng,CHEN Hai-tong,FANG Wei.Direct Adaptive Trajectory Linearization Control of Aerospace Vehicle Using SHLNN[J].Journal of Astronautics,2006,27(3):338-344,353.
Authors:ZHU Liang  JIANG Chang-sheng  CHEN Hai-tong  FANG Wei
Institution:College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Abstract:This paper presents a novel nonlinear adaptive control method based on trajectory linearization control method(TLC) and neural networks.TLC method is a novel nonlinear tracking and decoupling control way.However,inherent uncertainties may render it useless.In this paper,a neural network is used to cancels uncertainties through on-line learning.The adaptive law is designed based on Lyapunov approach,so all signal boundedness of the whole system is guaranteed.Finally,the flight control system of the aerospace vehicle is designed based on the proposed method and the simulation results demonstrate the excellent performance and robustness of the controllers.
Keywords:Flight control system  Trajectory linearization control  Neural networks  Adaptive control
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