Fang Shanxiang, Du Yao, Zhang Yong, Meng Fanbo, Ang Marcelo H
Department of Mathematics and Theory, Peng Cheng Laboratory, Shenzhen 518055, China.
Department of Mechanical Engineering, National University of Singapore, Singapore 117575, Singapore.
Micromachines (Basel). 2023 Mar 25;14(4):730. doi: 10.3390/mi14040730.
In order to satisfy the requirement of the automatic ultrasonic strengthening of an aviation blade surface, this paper puts forward a robotic compliance control strategy of contact force for ultrasonic surface strengthening. By building the force/position control method for robotic ultrasonic surface strengthening., the compliant output of the contact force is achieved by using the robot's end-effector (compliant force control device). Based on the control model of the end-effector obtained from experimental determination, a fuzzy neural network PID control is used to optimize the compliance control system, which improves the adjustment accuracy and tracking performance of the system. An experimental platform is built to verify the effectiveness and feasibility of the compliance control strategy for the robotic ultrasonic strengthening of an aviation blade surface. The results demonstrate that the proposed method maintains the compliant contact between the ultrasonic strengthening tool and the blade surface under multi-impact and vibration conditions.
为满足航空叶片表面自动超声强化的需求,本文提出一种用于超声表面强化的机器人接触力柔顺控制策略。通过构建机器人超声表面强化的力/位置控制方法,利用机器人末端执行器(柔顺力控制装置)实现接触力的柔顺输出。基于实验测定得到的末端执行器控制模型,采用模糊神经网络PID控制对柔顺控制系统进行优化,提高了系统的调节精度和跟踪性能。搭建实验平台验证航空叶片表面机器人超声强化柔顺控制策略的有效性和可行性。结果表明,所提方法在多冲击和振动条件下能保持超声强化工具与叶片表面的柔顺接触。