线性扩张状态观测滤波器的分析与应用-《郑州大学学报(工学版)》

文章信息/Info

Author(s):: Tan Panlong; Li Yimin; Zhao Xiangbin; Shao Xin; School of Intelligent Manufacturing, Sino-German University of Applied Sciences, Tianjin

Keywords:: Extended State Observer; filter; ADRC; powered parafoil; wind field identification

摘要:: 针对控制系统的输出容易受到噪声干扰的问题，提出了一种基于线性扩张状态观测器的滤波算法。线性扩张状态观测滤波器基于扩张状态观测器对系统状态和扩张状态的精确观测能力，不需要预先确定测量噪声的统计特征，即可对采样频率未知或者采样频率变化的系统输出进行滤波，而且结构简单，便于实现和进行调试。分析过程证明了扩张状态观测滤波器的收敛性，并给出了对应的离散表达式。仿真分析表明线性扩张状态观测滤波器与卡尔曼滤波器相比具有更快的计算速度和更高的滤波精度，因而更加实用。在动力翼伞系统风场辨识中的应用进一步说明了扩张状态观测滤波器的有效性。

Abstract:: A novel filtering method based on the extended state observer (ESO) is proposed according to the engineering practice that the system outputs are impact by measurement noise. The linear ESO (LESO) filter achieves noise reduction process based on the accurate observation ability of ESO. And the LESO filter doesn’t need the statistical characteristics of noise in its application and it is capable for control system outputs with unknown or varied sampling rate. The LESO filter is simple in structure with two tunable parameters and is suitable for embedded systems. Proof of the uniform convergence of the LESO for control systems with output measurement noise is presented in the analysis section. And the LESO filter is presented in discrete form. Simulation results reveals that the linear ESO filter outperforms the Kalman filter with less computing time and higher precision. Then the proposed filter is applied to the wind identification of the powered parafoil and payload system in landing area. The application shows that the LESO filter is effective and easy to use