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arXiv 2403.00076cs.RO

基于显式风速估计的非常规垂直起降无人机在前飞状态下的导航与控制

Navigation and Control of Unconventional VTOL UAVs in Forward-Flight with Explicit Wind Velocity Estimation

Mitchell Cohen, James Richard Forbes

AI总结:

针对非常规VTOL无人机前飞问题,提出基于IEKF的紧耦合风速与导航状态估计及SO(3)姿态控制分配方案,蒙特卡洛仿真验证了其鲁棒性。

摘要:

本文针对一类在前方飞行条件下运行的非常规垂直起降(VTOL)无人机,提出了一种状态估计与控制问题的解决方案。采用紧耦合状态估计方法来估计飞行器的导航状态、传感器偏置以及风速。状态估计在矩阵李群框架内利用不变扩展卡尔曼滤波器(IEKF)完成,与传统上在航空航天和机器人问题中使用的标准乘性扩展卡尔曼滤波器相比,该滤波器具有多项优势。采用基于SO(3)的姿态控制器,从而形成单一姿态控制律,无需单独的侧滑控制回路。利用控制分配器来确定如何使用多个(可能是冗余的)执行器以产生期望的控制力矩。风速估计被用于姿态控制器和控制分配器中以提升性能。通过一个具有四个控制面的尾座式VTOL无人机样例进行了数值算例验证。蒙特卡洛仿真表明,所提出的控制与估计方案对各种初始条件、噪声水平和飞行轨迹均具有鲁棒性。

英文摘要:

This paper presents a solution for the state estimation and control problems for a class of unconventional vertical takeoff and landing (VTOL) UAVs operating in forward-flight conditions. A tightly-coupled state estimation approach is used to estimate the aircraft navigation states, sensor biases, and the wind velocity. State estimation is done within a matrix Lie group framework using the Invariant Extended Kalman Filter (IEKF), which offers several advantages compared to standard multiplicative EKFs traditionally used in aerospace and robotics problems. An SO(3)- based attitude controller is employed, leading to a single attitude control law without a separate sideslip control loop. A control allocator is used to determine how to use multiple, possibly redundant, actuators to produce the desired control moments. The wind velocity estimates are used in the attitude controller and the control allocator to improve performance. A numerical example is considered using a sample VTOL tailsitter-type UAV with four control surfaces. Monte-Carlo simulations demonstrate robustness of the proposed control and estimation scheme to various initial conditions, noise levels, and flight trajectories.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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