Optimizing trajectory tracking control for hypersonic flight vehicles via ADDHP.

IF 6.5
Zhou Ziyang, Liang Xiaohui, Xu Bin
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引用次数: 0

Abstract

This article proposes an intelligent hybrid control strategy for hypersonic flight vehicles (HFVs) that integrates sliding mode control (SMC) with actor-dependent dual heuristic programming (ADDHP) to address trajectory tracking challenges. An SMC baseline controller is first developed to ensure stable tracking with model uncertainties. Additionally, a novel angle of attack (AOA) protection mechanism is designed, which maintains the AOA within constraint boundaries by generating smooth modifying signals. Furthermore, multiple ADDHP-based optimal compensators are then implemented in the velocity and altitude subsystems. These model-free compensators dynamically optimize control performance through error-driven learning, significantly improving tracking accuracy and adaptability in complex environments. Lyapunov stability analysis proves the convergence of both SMC and ADDHP. The effectiveness and superiority of the proposed strategy are validated through comparative simulations.

基于ADDHP的高超声速飞行器轨迹跟踪控制优化。
本文提出了一种将滑模控制(SMC)与参与者相关的双启发式规划(ADDHP)相结合的高超声速飞行器(hfv)智能混合控制策略,以解决轨迹跟踪问题。为了保证在模型不确定情况下的稳定跟踪,首先设计了一种SMC基准控制器。此外,设计了一种新的攻角保护机制,通过产生平滑的修正信号使攻角保持在约束边界内。然后,在速度和高度子系统中实现了多个基于addhp的最优补偿器。这些无模型补偿器通过错误驱动学习动态优化控制性能,显著提高了复杂环境下的跟踪精度和适应性。Lyapunov稳定性分析证明了SMC和ADDHP的收敛性。通过对比仿真验证了该策略的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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