摘要
四象限探测器存在较大测量噪声,严重影响快速反射镜(FSM)的跟踪性能和抗干扰能力。针对四象限探测器快速反射镜的控制问题,提出一种改进型自抗扰控制方法,利用卡尔曼滤波进行噪声滤波,扩张状态观测器负责系统状态和扰动的估计,并将观测出的总扰动加入卡尔曼滤波状态方程。最后,设计零相差跟踪控制器作为前馈控制器,并在dSPACE实验平台上进行控制性能实验与抗干扰能力实验。实验结果表明:改进型自抗扰控制器可以提高FSM的跟踪性能,以100 Hz正弦信号为例,相较于线性自抗扰控制和干扰观测器控制方法,跟踪精度分别提高了20.99%和65.40%;对10 Hz正弦扰动的抑制能力分别提升了35.36%和61.26%。所提改进型自抗扰控制方法可以在存在较大测量噪声的情况下实现对扰动的精确估计和抑制,有效提高FSM的控制性能。
Objective As an optical beam pointing control device, fast steering mirrors(FSMs) are crucial components of essential equipment used in various fields such as aerial imaging, laser communication, and space exploration. An FSM driven by a voice coil motor has the advantages of a large stroke and low driving voltage, and it is easy to control. Quadrant detectors(QDs) have been used in FSM systems as angle sensors due to their low cost and wide measuring range. However, QDs are greatly affected by both Johnson noise and background light noise, resulting in large measurement noise. An active disturbance rejection controller(ADRC), which can effectively estimate and compensate for disturbances and unmodeled dynamics, has been applied to FSMs to improve tracking performance. Large measurement noise contaminates estimations and degrades disturbance rejection performance. Large measurement noise thus poses a significant challenge in controlling FSMs. Therefore, improving the tracking performance and disturbance rejection capabilities of FSMs driven by voice coil motors with relatively larger measurement noise is critical.Methods An improved ADRC(IADRC) was proposed by combining a Kalman filter with a model-assisted extended state observer(MESO). First, the effects of the selected gain of the extended state observer on the performance of the ADRC were analyzed and revealed a trade-off between disturbance rejection and noise rejection(Fig. 3-4). Second, a model identification method based on the Hankel matrix was used to identify the exact model of the FSM(Fig. 5). An IADRC was then designed(Fig. 6) that primarily consisted of a Kalman filter, model-assisted ADRC, and zero-phase error tracking controller(ZPETC). The Kalman filter was used for noise filtering, and the necessary signal was input to the MESO. The MESO-observed lumped disturbance was then added to the Kalman filter state equation. The model-assisted active disturbance rejection controller was chiefly composed of an MESO under linear state error feedback contro
作者
张程鑫
孙崇尚
吴佳彬
张建强
李智斌
Zhang Chengxin;Sun Chongshang;Wu Jiabin;Zhang Jianqiang;Li Zhibin(College of Electrical Engineering and Automation,Shandong University of Science and Technology,Qingdao 266590,Shandong,China;Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,Jilin,China)
出处
《中国激光》
EI
CAS
CSCD
北大核心
2024年第13期175-183,共9页
Chinese Journal of Lasers
基金
山东省自然科学基金(ZR2021QF140,ZR2021QF117)
国家自然科学基金(U23A20336,52227811,61933006)。
关键词
光通信
快速反射镜
自抗扰控制
测量噪声
卡尔曼滤波器
optical communication
fast steering mirror
active disturbance rejection control
measurement noise
Kalman filter
