| 引用本文: | 秦华阳,陈增强,孙明玮,孙青林.基于滑动窗实时小波降噪的扩张状态观测器及自抗扰控制[J].控制理论与应用,2022,39(1):23~30.[点击复制] |
| QIN Hua-yang,CHEN Zeng-qiang,SUN Ming-wei,SUN Qing-lin.Extended state observer based on sliding window real-time wavelet denoising and active disturbance rejection control[J].Control Theory and Technology,2022,39(1):23~30.[点击复制] |
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| 基于滑动窗实时小波降噪的扩张状态观测器及自抗扰控制 |
| Extended state observer based on sliding window real-time wavelet denoising and active disturbance rejection control |
| 摘要点击 2564 全文点击 838 投稿时间：2020-08-09 修订日期：2020-11-20 |
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| DOI编号 10.7641/CTA.2021.00519 |
| 2022,39(1):23-30 |
| 中文关键词 自抗扰控制 滑动窗 扩张状态观测器 实时小波降噪 线性扩张状态观测器 |
| 英文关键词 active disturbance rejection control sliding window extended state observer real-time wavelet de-noising linear extended state observer |
| 基金项目 国家自然科学基金项目(61973175, 61973172)资助. |
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| 中文摘要 |
| 自抗扰控制技术应用已日渐成熟, 但当系统中存在高频非平稳噪声信号时, 线性自抗扰控制(LADRC) 存在
难以选取合适的观测器带宽的问题: 当带宽较小时, 线性扩张状态观测器(LESO)难以实现对总扰动的实时观测, 会
造成时滞; 当带宽较大时, LESO又会放大噪声对系统的影响, 从而造成总扰动观测失真. 为了解决这一问题, 将小
波降噪环节加入LADRC中, 通过设计基于滑动窗实时小波降噪的LESO, 对含噪输出信号进行实时降噪. 使用Simulink
搭建系统模型, 分别在输出信号中加入高斯白噪声或谐波等不同类型的高频非平稳噪声进行仿真实验, 并将所
提方法与滑动平均法进行对比, 结果验证了所提方法的有效性. |
| 英文摘要 |
| The application of active disturbance rejection control is becoming more and more mature. However, when
there exist high frequency non-stationary noise signals in the linear active disturbance rejection control (LADRC) system,
it is difficult to select the appropriate observer bandwidth. If the bandwidth is small, the linear extended state observer
(LESO) is unable to compensate the total disturbance in time, resulting in time delay. While the bandwidth is large,
LESO will amplify the impact of noise on the system. In order to solve this problem, wavelet de-noising link is added
to LADRC, and the noise output signal is de-noised in real time by designing LESO based on sliding window real-time
wavelet de-noising. The system model is built in Simulink, and different types of high-frequency non-stationary noises,
such as Gaussian white noise or harmonic noise, are added into the output signals respectively for simulation experiments,
and the proposed method is compared with the sliding average method. The effectiveness of the proposed method is verified
by the simulation results. |
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