Smith-RBF-PID在锻造操作机大车行走速度控制系统中的研究  

Research on Smith-RBF-PID in the Traveling Speed Control System of Forging Manipulator

作　　者：苗荣霞[1] 刘鑫森 杨婧 王磊[1] Miao Rongxia;Liu Xinsen;Yang Jing;Wang Lei(School of Electronic Information Engineering,Xi’an University of Technology,Shaanxi Xi’an 710000)

机构地区：[1]西安工业大学电子信息工程学院,陕西西安710000

出　　处：《南方农机》2022年第12期134-137,143,共5页

摘　　要：针对传统锻造操作机在作业过程中因自身惯量较大而导致行进速度不稳定的问题,本研究结合锻造操作机大车行走机构建立了其速度的动力学模型,采用基于径向基函数神经网络的PID控制与Smith预估器相结合的控制方法,实现对锻造操作机大车行走速度的精确控制。通过MATLAB/Simulink仿真对比分析得出:基于Smith-RBF-PID算法的控制效果与传统PID相比,其超调量以及调节时间都显著减小;与RBF-PID控制算法相比,缩短了响应时间,大大提高了操作机大车行走速度的控制精度。Aiming at the problem that the response lag of the traditional forging manipulator is relatively large due to its large inertia during the operation process,this study combines the forging manipulator trolley’s traveling mechanism to establish its speed dynamics model,and adopts the control method of the combination of PID control based on radial basis function neural network and Smith predictor to realize precise control of the traveling speed of the forging manipulator.By analyzing the simulation results of MATLAB/Simulink:it is concluded that the control effect based on Smith-RBF-PID arithmetic has obvious advantages over traditional PID in terms of over-adjustment and adjustment time;compared with the RBF-PID control algorithm,the response time is shortened,and the control accuracy of the walking speed of the operating machine has been improved to a greater extent.

关 键 词：锻造操作机 径向基函数神经网络 SMITH预估补偿 PID控制 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]