航空学报 > 2020, Vol. 41 Issue (11): 624387-624387   doi: 10.7527/S1000-6893.2020.24387

空天往返飞行器制导控制技术专栏

基于时标分解的弹性高超声速飞行器智能控制

许斌, 王霞   

  1. 西北工业大学 自动化学院, 西安 710072
  • 收稿日期:2020-06-08 修回日期:2020-07-09 出版日期:2020-11-15 发布日期:2020-09-02
  • 通讯作者: 许斌 E-mail:smileface.binxu@gmail.com
  • 基金资助:
    国家自然科学基金(61933010);陕西省自然科学基金(2019JZ-08);航空科学基金(20180753007,201905053005):霍英东教育基金(161058)

Time-scale decomposition based intelligent control of flexible hypersonic flight vehicle

XU Bin, WANG Xia   

  1. School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
  • Received:2020-06-08 Revised:2020-07-09 Online:2020-11-15 Published:2020-09-02
  • Supported by:
    National Natural Science Foundation of China (61933010); Natural Science Foundation of Shaanxi Province (2019 JZ-08); Aeronautical Science Foundation of China (20180753007, 201905053005); Fok Ying-Tong Education Foundation (161058)

摘要: 考虑弹性高超声速飞行器纵向动力学模型,提出了一种基于时标分解的智能控制方法。考虑刚体状态和弹性模态具有不同的时标特性,采用奇异摄动理论进行快慢时标分解,将模型转换为刚体慢变子系统和弹性快变子系统。针对刚体子系统考虑动力学不确定,基于平行估计模型构造表征不确定逼近效果的预测误差,结合跟踪误差给出复合学习控制策略。针对弹性子系统设计自适应滑模控制稳定弹性模态。通过李雅普诺夫稳定性分析可证系统状态一致终值有界。仿真表明所提出的控制方法能够实现刚弹模态的稳定收敛,且具有更高的跟踪精度、更好的学习性能和更快的收敛速度。

关键词: 高超声速飞行器, 弹性模态, 时标分解, 奇异摄动, 复合学习控制

Abstract: Considering the longitudinal dynamics of a flexible hypersonic flight vehicle, the time-scale decomposition based intelligent control is proposed. Considering the different time-scale characteristics between the rigid states and the flexible states, the singular perturbation theory is used to conduct the time-scale decomposition such that the vehicle model is transformed to the rigid slow dynamics and the flexible fast perturbation. For the rigid subsystem with dynamics uncertainty, based on the serial-parallel estimation model that can reflect the estimation performance, the prediction error is constructed and the composite learning control is designed. For the flexible subsystem, the adaptive sliding mode control is designed to stabilize the flexible states. The uniformly ultimately bounded stability of the system is proved via the Lyapunov stability analysis. The simulation test shows that the proposed method can guarantee the stable convergence of the whole system and achieve the higher tracking accuracy, the better learning performance and the faster convergence.

Key words: hypersonic flight vehicle, flexible states, time-scale decomposition, singular perturbation, composite learning control

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