• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Aerospace science and technology >Barrier Lyapunov function based reinforcement learning control for air-breathing hypersonic vehicle with variable geometry inlet
【24h】

Barrier Lyapunov function based reinforcement learning control for air-breathing hypersonic vehicle with variable geometry inlet

机译：基于障碍Lyapunov函数的进气可变进气道高超声速飞行器的强化学习控制

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Based on barrier Lyapunov functions, a reinforcement learning control method is proposed for air-breathing hypersonic vehicles with variable geometry inlet (AHV-VGI) subject to external disturbances and diversified uncertainties. The longitudinal dynamic for the AHV-VGI is transformed into strict feedback form. Controllers for velocity and altitude subsystems are designed, respectively. Taking advantage of the reinforcement learning strategy, two radial basis function (RBF) neural networks are applied to estimate the "total disturbances" in the flight control system. Actor network is used for generating the estimate of the disturbance. Critic network is used for evaluating the estimation accuracy. Prescribed tracking performances and state constraints can be guaranteed by introducing barrier Lyapunov functions (BLFs). Tracking differentiators are used to generate the derivatives of virtual controllers in the backstepping design process. Simulation results illustrate the effectiveness and advantages of the proposed control strategy. (C) 2019 Elsevier Masson SAS. All rights reserved.
机译：基于屏障李雅普诺夫函数，提出了一种受外部干扰和不确定性影响的具有可变几何进气口（AHV-VGI）的超音速呼吸飞机的强化学习控制方法。 AHV-VGI的纵向动态转换为严格的反馈形式。分别设计了速度和高度子系统的控制器。利用强化学习策略，应用了两个径向基函数（RBF）神经网络来估计飞行控制系统中的“总扰动”。 Actor网络用于生成干扰估计。批判网络用于评估估计准确性。引入屏障Lyapunov函数（BLF）可以保证规定的跟踪性能和状态约束。跟踪微分器用于在后推设计过程中生成虚拟控制器的派生类。仿真结果说明了所提出控制策略的有效性和优势。 （C）2019 Elsevier Masson SAS。版权所有。

著录项

  • 来源
    《Aerospace science and technology》 |2020年第1期|105537.1-105537.12|共12页
  • 作者

  • 作者单位

    Beijing Simulat Ctr Sci & Technol Special Syst Simulat Lab Beijing 100854 Peoples R China|Beihang Univ Sch Aeronaut Sci & Engn Beijing 100191 Peoples R China;

    Beihang Univ Sch Aeronaut Sci & Engn Beijing 100191 Peoples R China;

    High Tech Inst Xian Dept Automat Xian 710025 Peoples R China;

    Beijing Aerosp Automat Control Inst Beijing 100854 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hypersonic vehicle; Variable geometry inlet; Reinforcement learning; Barrier Lyapunov function; Performance-guaranteed tracking;

    机译：高超音速飞行器;可变几何形状的入口;强化学习;屏障李雅普诺夫函数;性能保证的跟踪;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号