Kalman滤波算法在海洋钻机中控制信号的优化  

Optimization of Control Signal of Kalman Filter Algorithm in Marine Drilling Rig

作　　者：刘浩 魏立鑫 尤立春 LIU Hao;WEI Lixin;YOU Lichun(Tianshui Electric Transmission Research Institute Group Co.,Ltd.,Tianshui 741000,Gansu,China;State Key Laboratory of Large Electric Drive System and Equipment Technology,Tianshui 741000,Gansu,China)

机构地区：[1]天水电气传动研究所集团有限公司,甘肃天水741000 [2]大型电气传动系统与装备技术国家重点实验室,甘肃天水741000

出　　处：《电气传动》2023年第11期19-24,30,共7页Electric Drive

基　　金：甘肃省教育厅产业支撑计划项目(2021CYZC-42);天水市科技重大专项计划(2022-GXJSK-4842)。

摘　　要：海洋钻机由于其应用的特殊性,对控制信号的稳定程度及控制精度有更高的要求。针对海洋钻机电控系统中信号受噪声干扰大的情况,提出一种基于Kalman滤波算法的PID控制信号优化方式,控制过程中信号是多维且非平稳输出,利用Matlab/Simulink软件仿真PID传递函数并整定参数,利用传递控制信号的输出作为Kalman滤波算法线性观测方程的输入,运行正态分布融合模型,建立海洋钻机控制信号的干扰高斯白噪声的模型,对稳定信号及噪声观测值进行加权平均更新迭代计算,以便于获取最小方差估计值,从而得到降噪的信号。实验仿真表明,与传统的PID信号输出相比较,系统具备更强的抗干扰能力和更好的鲁棒性。Due to the particularity of its application,offshore drilling rig has higher requirements for the stability and control accuracy of the control signal.Aiming at the situation that the signal in the electronic control system of offshore drilling rig is greatly disturbed by noise,a PID control signal optimization method based on Kalman filtering algorithm was proposed.The signal is multidimensional and non-stationary output in the control process.The PID transfer function was simulated by Matlab/Simulink software.The output of the transmitted control signal was used as the input of the linear observation equation of the Kalman filtering algorithm.The normal distribution fusion model was run to establish the model of Gaussian white noise interference of the control signal of offshore drilling rig.The weighted average update iterative calculation of the stable signal and noise observation value was carried out to obtain the minimum variance estimation value,so as to obtain the noise reduction signal.The experimental simulation shows that compared with the traditional PID signal output,the system has stronger anti-interference ability and better robustness.

关 键 词：Kalman滤波算法 正态融合模型 自整定PID模型 高斯白噪声 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]