摘要
在智能制造领域,数控机床最终加工出来的产品质量除了与机床本身性能有关外更重要的是进给系统的伺服优化效果。为提高数控机床进给伺服系统优化效果,设计了一种基于BP神经网对数控机床进给系统PID控制器进行优化的模型。利用BP神经网络具有逼近任意非线性函数的特点,通过对系统性能优化算法实现最佳PID参数组合。Matlab/Simulik仿真实验结果表明,BP-PID控制器能够快速、有效地对非线性数控机床进给系统进行控制,对提高机床加工精度具有重要意义。
In the field of intelligent manufacturing,the CNC machine tool plays an important role in production equipment.The final product quality is not only related to the performance of the machine tool itself,but also the servo optimization effect of the feed system.In order to improve the optimization effect,a model to optimize the PID controller of NC machine tool feed system is designed based on the BP neural network in this paper.By using the characteristics of approaching any nonlinear function of the BP neural network,the optimal PID parameter combination is realized by optimizing the system performance algorithm.The Matlab/Simulik simulation results show that BP-PID controller can quickly and effectively control the feed system of nonlinear NC machine tool,which is of great significance to improve the machining accuracy of machine tool.
作者
王远涛
张俊男
宋寿鹏
WANG Yuan-tao;ZHANG Jun-nan;SONG Shou-peng(Department of Materials Engineering,Liaoning Mechatronics College,Dandong Liaoning 118009,China)
出处
《机械研究与应用》
2022年第2期55-58,共4页
Mechanical Research & Application
基金
辽宁机电职业技术学院科研项目:基于(HNC-CS)数控铣床的大赛设备开发(编号:ky202109)
辽宁机电职业技术学院科研项目:采煤机滚动轴承状态检测关键技术的研究(编号:ky202106)。
