arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1503.02718math.OC
收藏

基于类线性互补滤波器的姿态估计与控制:理论与实验

Attitude Estimation and Control Using Linear-Like Complementary Filters: Theory and Experiment

L. Benziane, A. El Hadri, A. Seba, A. Benallegue, Y. Chitour

摘要:

提出了一种基于线性互补滤波器原理的融合惯性矢量测量的姿态估计与控制新算法。首先,提出了n阶直接和无源互补滤波器与TRIAD算法相结合的姿态估计方案。对于噪声有效的这些解决方案包括陀螺仪偏差估计。此后,相同的数据融合的原则被用来解决基于惯性矢量测量的姿态跟踪问题。因此,代替在控制律中使用有噪声的原始测量,提出了包括线性互补滤波器以处理噪声的新的控制解决方案。基于LaSalle不变性定理的跟踪误差动力学的稳定性分析证明了几乎所有的轨迹渐近收敛到期望的平衡点。实验结果表明,所提出的解决方案的有效性和性能的DIY四配备了APM 2.6自动驾驶仪。

英文摘要:

This paper proposes new algorithms for attitude estimation and control based on fused inertial vector measurements using linear complementary filters principle. First, n-order direct and passive complementary filters combined with TRIAD algorithm are proposed to give attitude estimation solutions. These solutions which are efficient with respect to noise include the gyro bias estimation. Thereafter, the same principle of data fusion is used to address the problem of attitude tracking based on inertial vector measurements. Thus, instead of using noisy raw measurements in the control law a new solution of control that includes a linear-like complementary filter to deal with the noise is proposed. The stability analysis of the tracking error dynamics based on LaSalle's invariance theorem proved that almost all trajectories converge asymptotically to the desired equilibrium. Experimental results, obtained with DIY Quad equipped with the APM2.6 auto-pilot, show the effectiveness and the performance of the proposed solutions.

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。

↑