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<p>Multi-source uncertainties inherent in quadrotor unmanned aerial vehicle (QUAV) systems critically impact attitude tracking control performance and operational safety. This study establishes a comprehensive framework to systematically investigate uncertainty propagation mechanisms in QUAV attitude dynamics while developing quantitative reliability evaluation indices for safety-critical system optimization. We propose an interval Linear Quadratic Tracking control framework incorporating state reliability constraints to achieve robust optimal performance. The main contributions include: (1) formulation of an interval state-space equation for QUAV dynamics with parametric uncertainties; (2) development of an interval Riccati-equation-based optimization core enabling rigorous analysis of cost function bounds, control input ranges, and state response envelopes under uncertainty propagation; (3) establishment of novel non-probabilistic time-dependent reliability indices through first-passage probability theory for quantitative safety assessment of uncertain control systems. The proposed method enables concurrent optimization of control performance and system reliability through constrained interval optimization. Numerical example of QUAV attitude tracking scenarios demonstrate the effectiveness of the proposed method, confirming the superior robustness and safety characteristics of the proposed design.</p>

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Uncertain attitude tracking control for QUAV based on interval LQT with states reliability constraints

  • 期刊论文

  • 发表日期：

    2025年5月20日

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  • Chen Yang,
  • Yuanhang Zuo,
  • Wanze Lu,
  • Taiqi Wang

摘要

Multi-source uncertainties inherent in quadrotor unmanned aerial vehicle (QUAV) systems critically impact attitude tracking control performance and operational safety. This study establishes a comprehensive framework to systematically investigate uncertainty propagation mechanisms in QUAV attitude dynamics while developing quantitative reliability evaluation indices for safety-critical system optimization. We propose an interval Linear Quadratic Tracking control framework incorporating state reliability constraints to achieve robust optimal performance. The main contributions include: (1) formulation of an interval state-space equation for QUAV dynamics with parametric uncertainties; (2) development of an interval Riccati-equation-based optimization core enabling rigorous analysis of cost function bounds, control input ranges, and state response envelopes under uncertainty propagation; (3) establishment of novel non-probabilistic time-dependent reliability indices through first-passage probability theory for quantitative safety assessment of uncertain control systems. The proposed method enables concurrent optimization of control performance and system reliability through constrained interval optimization. Numerical example of QUAV attitude tracking scenarios demonstrate the effectiveness of the proposed method, confirming the superior robustness and safety characteristics of the proposed design.