增强型ERG控制框架:模块设计与性能实证(先进飞行器安全控制专栏)

  • 金宇 ,
  • 杨夏 ,
  • 张雷 ,
  • 唐家成 ,
  • 朱波
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  • 1. 中山大学
    2. 南京大学

收稿日期: 2025-06-24

  修回日期: 2025-12-28

  网络出版日期: 2025-12-29

基金资助

国家自然科学基金;国家重点研发计划课题

Enhanced ERG-based Control Framework: Module Design and Experimental Validation

  • JIN Yu ,
  • YANG Xia ,
  • ZHANG Lei ,
  • TANG Jia-Cheng ,
  • ZHU Bo
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Received date: 2025-06-24

  Revised date: 2025-12-28

  Online published: 2025-12-29

摘要

基于显式参考管理器(Explicit Reference Governor,ERG)的控制框架在航空航天领域展现出显著的应用潜力,其核心优势体现在以有限计算资源实现多约束条件下的安全控制。然而,其实际效能依赖于动态安全裕度计算的准确性与保守性。本研究以模型不确定的二自由度直升机控制平台为对象,提出融合最低阶不确定性与干扰估计器(Uncertainty and Disturbance Estimator,UDE)和风险评估模块的增强型ERG框架。该框架通过两个关键设计实现性能突破:1)引入UDE实现对不确定因素的主动补偿,提升基于标称模型的轨迹预测精度,确保动态安全裕度的可靠计算;2)嵌入风险评估模块,以避免辅助参考(Auxiliary Reference,AR)过保守过渡引起的系统响应变慢。通过多组仿真和实物对比实验验证了:增强后的框架保留了固有优点,解决了对模型精度敏感、辅助参考调整保守的问题,同时实现了稳态误差降低和响应速度提升。

本文引用格式

金宇 , 杨夏 , 张雷 , 唐家成 , 朱波 . 增强型ERG控制框架:模块设计与性能实证(先进飞行器安全控制专栏)[J]. 航空学报, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2025.32465

Abstract

The control framework based on the Explicit Reference Governor (ERG) demonstrates significant application potential in the aerospace field, with its core advantage lying in achieving safety control under multiple constraints with limited computational resources. However, its practical effectiveness depends on the accuracy and conservatism of dynamic safety margin calculations. Focusing on a two-degree-of-freedom (2-DOF) helicopter control platform with model uncertainties, this study proposes an enhanced ERG framework integrating a lowest-order Uncertainty and Disturbance Estimator (UDE) and a risk assessment module. The framework achieves performance breakthroughs through two key designs: 1) The introduction of the UDE to actively compensate for uncertainties, thereby improving the accuracy of trajectory prediction based on the nominal model and ensuring reliable dynamic safety margin calculation. 2) The embedding of a risk assessment module to avoid system response delays caused by overly conservative transitions of the Auxiliary Reference (AR). Multiple sets of simulation and physical comparative experiments verify that the enhanced framework retains inherent advantages while solving the problems of sensitivity to model accuracy and conservative auxiliary reference adjustments, simultaneously achieving reduced steady-state error and increased response speed.

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