摘要
为了提高折弯送料机器人的定位精度,采用遗传算法优化折弯送料机器人PID控制参数。创建折弯送料机器人折弯板材装置简图,采用增量式PID控制方程式。确定PID控制参数优化变量,采用遗传算法优化PID控制参数,给出遗传算法优化PID控制器参数的具体过程,设计PID在线调优流程。采用MATLAB软件对折弯送料机器人角位移运动误差进行仿真,输出误差变化曲线。并且,与优化前折弯送料机器人PID控制效果进行对比和分析。结果表明,折弯送料机器人连杆1、连杆2和连杆3最大误差分别从1.73×10^(-3)rad、1.91×10^(-3)rad和2.03×10^(-3)rad降低到0.42×10^(-3)rad、0.48×10^(-3)rad和0.55×10^(-3)rad,下降了75.7%、74.9%和72.9%。采用遗传算法优化增量式PID控制参数设计变量,能够提高折弯送料机器人的定位精度。
In order to improve the positioning accuracy of the bending feeding robot, a genetic algorithm is used to optimize the PID control parameters of the bending feed robot. A bending device for bending feeding robot is created, and the incremental PID control equation is adopted. The optimization variables of PID control parameters are determined, genetic algorithm is used to optimize PID control parameters, and the specific process of optimizing PID controller parameters by genetic algorithm is given, and the online tuning process of PID is designed. MATLAB software is used to simulate the angular displacement motion error of the bending feeding robot and output error variation curve. Moreover, the PID control effect of the optimized bending robot is compared and analyzed. The results show that the maximum errors of the connecting rod 1, connecting rod 2 and connecting rod 3 are reduced from 1.73×10 -3 rad, 1.91×10 -3 rad and 2.03×10 -3 rad to 0.42×10 -3 rad, 0.48×10 -3 rad and 0.55×10 -3 rad respectively, down by 75.7%, 74.9% and 72.9%. Genetic algorithm is used to optimize the design variables of the incremental PID control parameters, which can improve the positioning accuracy of the bending feeding robot.
作者
孙素海
SUN Su-hai(Anhui Zhongjia Automation Technology Co.Ltd,Chuzhou 239000,China)
出处
《佳木斯大学学报（自然科学版）》
CAS
2018年第5期744-746,768,共4页
Journal of Jiamusi University：Natural Science Edition
