北京航空航天大学学报 ›› 2009, Vol. 35 ›› Issue (9): 1144-1147.

• 论文 • 上一篇    下一篇

基于遗传算法的高速飞行器滑模控制律设计

李惠峰, 王 健, 孙文冲   

  1. 北京航空航天大学 宇航学院, 北京 100191
  • 收稿日期:2008-09-17 出版日期:2009-09-30 发布日期:2010-09-14
  • 作者简介:李惠峰(1970-),女,陕西蒲城人,副教授,leehuifeng@buaa.edu.cn.

GA based design of sliding mode control law for hypersonic vehicle

Li Huifeng, Wang Jian, Sun Wenchong   

  1. School of Astronautics, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2008-09-17 Online:2009-09-30 Published:2010-09-14

摘要: 以高超声速飞行器GHV(Generic Hypersonic Vehicle)的俯仰通道为控制对象,针对其6自由度非线性模型设计了滑模控制律.为了便于应用滑模控制理论,首先对该模型进行了输入输出反馈线性化,将原模型转换成为仿射型.设计好滑模控制律结构以后,基于遗传算法完成了滑模控制律参数设计.该过程利用了随机鲁棒思想,即在随机均匀分布的参数不确定性作用下,通过遗传算法优化滑模控制律参数,使得飞行控制系统失去稳定性和鲁棒性的概率达到最小.仿真表明,该方法可以同时满足飞行控制系统鲁棒性和参数优化过程收敛性的要求.

Abstract: A sliding mode control law was presented according to the six DOF nonlinear model of pitching channel of hypersonic vehicle generic hypersonic vehicle(GHV). First, for making a good use of sliding mode control theory, the six DOF model was transformed into an affine system through input-output feedback linearization. Then, the structure of sliding mode control law was designed for the affine system. After the structure design of sliding mode control law, the control parameters of sliding mode control law were designed based on genetic algorithm. The design process of sliding mode control parameters takes into account stochastic robustness strategy, which is to make sure that the possibility of loss of flight control stability or robustness achieves least through control parameter optimization based on genetic algorithm, when dealing with parameter uncertainties in stochastic uniform distribution. Simulations show that the method is able to satisfy both the robustness of flight control system and the convergence of parameter optimization process on request.

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