基于卡尔曼模糊自适应PID的激光雷达斩光频率控制方法

J4 ›› 2018, Vol. 35 ›› Issue (5): 608-617.

基于卡尔曼模糊自适应PID的激光雷达斩光频率控制方法

王贤宇1,2, 方欣1,2*, 李陶1

1中国科学技术大学地球和空间科学学院，中国科学院近地空间环境重点实验室，安徽合肥 230026; 2中国科学院空间天气学国家重点实验室, 北京100190

收稿日期:2017-07-24 修回日期:2017-08-24 出版日期:2018-09-28 发布日期:2018-09-29
通讯作者: 李陶（1974—），安徽巢湖人，博士，教授，主要从事激光雷达系统及中高层大气方面的研究。 E-mail:litao@ustc.edu.cn
基金资助:
Supported by National Natural Science Foundation of China（国家自然科学基金, 41127901，41304122），Specialized Research Fund for State Key Laboratories（国家重点实验室专项基金资助项目, 2016-93F-04

Chopping frequency control method in lidar system based on Kalman fuzzy adaptive PID

WANG Xianyu1,2, FANG Xin1,2*, LI Tao1

1 Key Laboratory of Geospace Enviroment of Chinese Academy of Sciences, School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China) 2 Sate Key Laboratory of Space Weather, Chinese Academy of Sciences, Beijing 100190, China

Received:2017-07-24 Revised:2017-08-24 Published:2018-09-28 Online:2018-09-29

摘要/Abstract

摘要：

为提高激光雷达回波信号斩光高度的稳定性，针对臭氧探测激光雷达系统后继光路中直流无刷电机的高转速高转矩控制系统，提出了模糊自适应PID控制方法。通过模糊推理实现不同状态下PID参数的在线自动整定，并利用卡尔曼滤波减少控制噪声和测量噪声的干扰。基于控制理论，利用Matlab软件进行控制算法性能模拟，并利用LabVIEW平台实现系统的控制算法。结果表明与普通PID控制方法相比，基于模糊自适应PID控制方法的激光雷达斩光频率阶跃响应调节时间减少33.3%，延迟时间短60%，上升时间短42.1%，斩光盘的频率抖动仅约为0.0492 Hz。模糊自适应PID控制系统稳态误差更小，有更好的适应性、稳健性和抗干扰性。

关键词: 直流无刷电机；模糊自适应PID；卡尔曼滤波；LabVIEW；激光雷达；斩光频率

Abstract:

n order to improve the stability of chopping height of lidar echo signal, a fuzzy self-adaptive PID control method is proposed for the high speed and high torque control system of DC brushless motor in the subsequent optical path of ozone detection lidar system. On-line automatic tuning of PID parameters in different states by fuzzy reasoning is realized, and Kalman filter is used to reduce the interference of control and measurement noise. Based on control theory, performance simulation of the control algorithm is carried out using Matlab software, and control algorithm of the system is realized in LabVIEW software platform. Results show that compared with the conventional PID control method, step response time of laser chopping frequency based on the fuzzy self-adaptive PID control method is reduced by 33.3%, delay time is shorten by 60%, and rise time is reduced by 42.1%. The frequency jitter of chopper disc is only about 0.0492 Hz. The fuzzy self-adaptive PID control system has smaller steady state error, better adaptability and robustness, and better anti-interference performance.

Key words: DC brushless motor; fuzzy self-adaptive PID; Kalman filter; LabVIEW; lidar; chopping frequency

王贤宇方欣李陶. 基于卡尔曼模糊自适应PID的激光雷达斩光频率控制方法[J]. J4, 2018, 35(5): 608-617.

参考文献

[1] Li Zhuo, Xiao Deyun, He Shizhong. Self tuning PID controller based on Fuzzy inference [J]. Control Theory and Applications(控制理论与应用), 1997, 2: 238-243(in Chinese). [2] Zhao Baochun, Luo Zongan, Liu Xianghua. Design and simulation of Fuzzy logic controller based on LabVIEW[J]. Control Engineering of China(控制工程), 2006, S1: 53-56(in Chinese). [3] Shadkam M, Mojallali H, Bostani Y. Speed control of DC motor using extended Kalman filter based Fuzzy PID[J]. International Journal of Information and Electronics Engineering, 2013, 3(1)：109-112. [4] Liu Jun, Chen Wuwei. Study on EPS using Fuzzy and PID multi-mode control with Kalman filter[J]. Transactions of The Chinese Society of Agricultural Machinery(农业机械学报), 2007, 38(9): 1-5(in Chinese). [5] Xia Changliang. Brushless DC Motor Control System(无刷直流电机控制系统)[M]. Beijing: Science Press, 2009(in Chinese). [6] Duan X G, Li H X, Deng H. Robustness of fuzzy PID controller due to its inherent saturation[J]. Journal of Process Control, 2012, 22(2): 470-476. [7] Ahn K K, Truong D Q. Online tuning fuzzy PID controller using robust extended Kalman filter[J]. Journal of Process Control, 2009, 19(6): 1011-1023. [8] LabVIEW NI, PID and Fuzzy Logic Toolkit User Manual[M]. http://www.ni.com/pdf/manuals/PID_2013readme_KB.html, 2009. [9] Yao G, Gao F, Wang C, et al. Design and simulation based on Kalman filter fuzzy adaptive PID control for mold liquid level control system[C]//Control and Decision Conference, 2009. CCDC'09. Chinese. IEEE, 2009: 6105-6109. [10] Salim, Ohri J. Fuzzy based PID controller for speed control of DC motor using LabVIEW[J]. Wseas Transactions on Systems and Control, 2015, 10: 154-159. [11] Thepsatorn P, Numsomran A, Tipsuwanporn V, et al. DC motor speed control using Fuzzy logic based on LabVIEW[C]. SICE-ICASE, 2006 International Joint Conference, 2006: 3617-3620.