模型预测控制在抛光机器人推推中的应用

Nobuaki Endo, T. Yoshimi, Koichiro Hayashi, H. Murakami
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引用次数: 0

摘要

许多抛光工作是由熟练工人手工完成的。教机器人完成它们的详细工作并配置和操作一个适当的控制系统来实现这一目标并不容易,而且这一过程的自动化已经推迟。抛光是通过将旋转工具压在要加工的工件上来完成的。为了实现这种运动,许多机器人的控制器都采用了PID控制。但要确定合适的控制增益,需要根据加工目标和加工条件反复调整控制增益。本研究的目的是介绍模型预测控制(MPC)作为一种新的抛光机器人控制系统。MPC是一种使用控制目标模型来预测控制输出的控制。因此,我们认为当力条件即加工条件发生变化时,在不改变MPC参数的情况下可以实现目标力值。本文在MATLAB Simulink中创建了控制框图,实现了MPC的应用。然后将方框图安装在实际机器上,检查是否可以用适当的力按压,并评估与PID的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Model Predictive Control to Polishing Robot for Pushing Operation
Much of the polishing work is done manually by skilled workers. It is not easy to teach robots to perform the detailed work of theirs and to conFigure and operate an appropriate control system to achieve this, and automation of this process has been delayed. Polishing is performed by pressing a rotating tool against the workpiece to be machined. To achieve this motion, PID control is used in the controllers of many robots. However, to determine the appropriate control gain, it is necessary to repeatedly adjust the control gain according to the processing target and processing conditions. The purpose of this research is to introduce Model Predictive Control (MPC) as a new control system for polishing robots. MPC is a control that predicts control output using a model of the control target. Therefore, we considered the target force value could be achieved without changing the MPC parameters when the force condition, a machining condition, is changed. In this paper, control block diagrams were created in MATLAB Simulink to apply MPC. The block diagram was then mounted on the actual machine to check whether it could be pressed with appropriate force, and the differences from PID were evaluated.
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