针对全向无人机的执行器非对称性，提出滚动时域优化分配策略。
Receding-Horizon Nullspace Optimization for Actuation-Aware Control Allocation in Omnidirectional UAVs
- 基于滚动时域与零空间优化，显式建模电机非对称动态
- 仿真显示电机指令振荡减少，位置与姿态跟踪性能提升
- 适合高机动飞行与空中交互任务的全向无人机控制
全驱动全向无人机可独立控制六个自由度上的力与力矩，拓展了敏捷飞行和空中交互任务的操作范围。然而，传统控制分配方法忽视机载执行器的非对称动态特性，导致动态机动时出现电机指令振荡，降低轨迹跟踪精度。本文提出一种滚动时域、执行器感知的分配策略，显式融入非对称电机动态，并通过零空间优化利用过驱动平台的冗余性。通过在预测时域内前向仿真闭环系统，该方法能预判并抑制由执行器引起的振荡，同时精确保持期望的机体合力偶。该方法被建模为约束最优控制问题，通过约束迭代LQR在线求解。在OmniOcta平台的仿真结果表明，与传统的单步二次规划分配器相比，该方法显著减少了电机指令振荡，提升了位置与姿态的轨迹跟踪性能。
原文摘要 · Abstract (English)
Fully actuated omnidirectional UAVs enable independent control of forces and torques along all six degrees of freedom, broadening the operational envelope for agile flight and aerial interaction tasks. However, conventional control allocation methods neglect the asymmetric dynamics of the onboard actuators, which can induce oscillatory motor commands and degrade trajectory tracking during dynamic maneuvers. This work proposes a receding-horizon, actuation-aware allocation strategy that explicitly incorporates asymmetric motor dynamics and exploits the redundancy of over-actuated platforms through nullspace optimization. By forward-simulating the closed-loop system over a prediction horizon, the method anticipates actuator-induced oscillations and suppresses them through smooth redistribution of motor commands, while preserving the desired body wrench exactly. The approach is formulated as a constrained optimal control problem solved online via Constrained iterative LQR. Simulation results on the OmniOcta platform demonstrate that the proposed method significantly reduces motor command oscillations compared to a conventional single-step quadratic programming allocator, yielding improved trajectory tracking in both position and orientation.
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