## 5 Verification Experiments  
### Verification of the ARGW System Dynamics Model  
To verify the accuracy of the dynamics model and the effectiveness of the configuration optimization method, the experimental platform is built in Figure 13. The milling robot is KR 210 R2700, and the workpiece milling surface is 6061 aluminum alloy. In the middle of the clamping robot flange and gripper is a six-dimensional force sensor that can be used to collect the forces applied on the clamping robot during milling. In addition, the clamping status of the workpiece by the gripper can be monitored using the data on the force sensor. When the configuration of the clamping robot remains unchanged, the data of the force sensor after clamping is equal to the previous clamping, it means that the clamping force of the workpiece is consistent and determined by the gripper. In this way, the influence of the clamping force on the vibration suppression effect is excluded. Moreover, the responses of the workpiece are collected by the three-component acceleration sensor and DHDAS dynamic signal collector.  
In the verification experiment, the \([x_{\rm end},y_{\rm end},z_{\rm end},Rx,Ry,Rz]\) of the clamping robot were [0.78 m, 0.36 m, 1.03 m, 140.79\({}^{\circ}\), 67.89\({}^{\circ}\), 40.54\({}^{\circ}\)]. The workpiece was milled using the process parameters in Table 1, and the responses of the workpiece in the experiment were collected using the acceleration sensor. The forces information collected by the force sensor is converted into the \(o_{w}x_{w}y_{w}z_{w}\) coordinate system, and the forces are presented in Figure 14 after compensating the initial forces information and gravity. In general, the feed and radial forces are greater than the axial forces. Since the milling direction in this paper is the negative direction of \(z_{\rm w}\), the forces in \(x_{\rm w}\) and \(z_{\rm w}\) directions are significantly greater than those in \(y_{\rm w}\) direction. By inputting the milling forces into the ARGW system dynamics model, the workpiece acceleration response can be obtained. Compared with the responses collected by the acceleration sensor, the results are shown in Figure 15.  
Figure 13: The experimental platform.  
Figure 15a-c presents the responses in the \(x_{\rm w}\), \(y_{\rm w}\), and \(z_{\rm w}\) directions, respectively. From the acceleration responses in the three directions, it can be seen that the responses increase rapidly and then decrease at the beginning stage, and the responses in the middle stage tend to be stable, finally decreasing slowly at the end stage. This is because when the tool  
Figure 14: Milling forces in \(x_{\rm w}\), \(y_{\rm w}\), and \(z_{\rm w}\) directions.  
Figure 15: Responses of the experiment and simulation: (**a**) \(x_{\rm w}\) direction, (**b**) \(y_{\rm w}\) direction, (**c**) \(z_{\rm w}\) direction.  
first enters the workpiece, the instantaneous excitation will make the workpiece produce a large response. As the tool moves away from the workpiece, the response decreases as the amount of cutting decreases. It can be seen from the local magnification diagram that the responses of the experiment and the simulation agree well overall. Specifically, the maximum error is 4.6 m/s\({}^{2}\), appearing in the \(x_{\text{w}}\) direction, whereas the average errors in the three directions are only 2.9%, 3.4%, and 2.3%. The comparative results demonstrate the accuracy of the dynamics model of the ARGW system. Moreover, the simulated responses are always smaller than the experimental responses in either direction. This is because there are various environmental noises in the experiment, while the simulation is carried out in an ideal environment without additional interfering factors.