Risley双棱镜与FSM复合轴实时精密控制技术研究
马秀刚，张文博，陶冶*
（四川大学 机械工程学院，四川 成都 610065）
摘要：针对单探测器复合轴粗精控制方法粗精平台交接换班工作控制复杂、解耦难度大、响应速度慢、控制精度低等问题，本文提出了一种Risley双棱镜与FSM复合轴实时精密控制方法。该方法基于Risley双棱镜与FSM光束指向理论实现了复合轴Risley双棱镜粗跟踪轴的偏差实时预测与精密补偿控制。构建了包括粗跟踪、预测偏差、精跟踪三个模块的复合轴跟踪系统模型，利用RBF神经网络模型提前预测Risley双棱镜粗跟踪平台下一个控制周期的跟踪误差，并通过FSM对此误差进行实时补偿，提高复合轴系统跟踪精度。为验证方法有效性，在MATLAB仿真环境下对本文提出的Risley双棱镜与FSM快反镜复合轴实时精密控制方法与传统复合轴控制方法进行了对比试验，结果表明本文方法有效提高了复合轴系统的跟踪精度与响应速度，将复合轴稳定跟踪误差从4.88 µrad降低到0.89 µrad。
关键词：Risley双棱镜；FSM；粗精控制；复合轴；RBF神经网络
中图分类号：O353.5 文献标志码：A doi：10.3969/j.issn.1006-0316.2022.06.004
文章编号：1006-0316 (2022) 06-0022-10
Research on Real-Time Precision Control Technology of Composite Axis of Risley Double Prisms and FSM
MA Xiugang，ZHANG Wenbo，TAO Ye
( School of Mechanical Engineering, Sichuan University, Chengdu 610065, China )
Abstract：Aiming at the problems of complex control of the shift of the coarse and fine tracking platforms, difficult decoupling, slow response speed and low control accuracy of typical single detector composite axis coarse and fine control methods, a real-time precision control method of Risley double prisms and FSM composite axis is proposed in this paper. On the basis of the beam pointing theory of Risley double prisms and FSM, this method realizes the real-time prediction and precision compensation control of the deviation of the spindle of the composite axis Risley double prisms. The composite axis tracking system model consisting of the modules of coarse tracking, error prediction and fine tracking is built. The RBF neural network model is used to predict the tracking error of the next control cycle of the Risley double prisms coarse tracking platform in advance, and the error is compensated in real time through the FSM fine tracking platform, so as to improve the tracking accuracy of the composite axis system. In order to verify the effectiveness of the method, a comparative simulation experiment between the traditional composite axis control method and the control method proposed in this paper is designed in the MATLAB environment. The experimental results show that the control method effectively improves the response speed of the composite axis system and reduces the stable tracking error of the composite axis from 4.88 µrad to 0.89 µrad.
Key words：Risley double prisms；FSM；coarse and fine control；compound axis；RBF neural network
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收稿日期：2022-01-25
基金项目：四川省科技计划重点研发项目（2021YFG0193）；四川大学－达州市人民政府校市战略合作专项项目（2020CDDZ-05）
作者简介：马秀刚（1995－），男，彝族，四川凉山人，硕士研究生，主要研究方向为机械设计制造及其自动化，E-mail：1624345995@qq.com。*通讯作者：陶冶（1984－），男，辽宁抚顺人，博士，副教授，主要研究方向为复杂机电系统精密测量与控制、创新设计理论与方法等，E-mail：yetao@scu.edu.cn。
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