基于卡尔曼模糊自适应PID的激光雷达斩光频率控制方法

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

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,用Matlab软件进行控制算法性能模拟,并用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.

In 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 Lab VIEW 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 about0.0492 Hz. The fuzzy self-adaptive PID control system has smaller steady state error, better adaptability and robustness, and better anti-interference performance.