Research on Force Control Based on Sim2Real Transfer for Stiffness of Thin-walled Parts

doi:10.3901/JME.2021.17.053

Abstract

Abstract: Complex thin-walled parts are widely used in aerospace field. However, due to its complex structure, small wall thickness and deformability, it is difficult to realize constant force control in the process of machining. As a result, the machining accuracy of parts is difficult to meet the requirements. Impedance control provides an effective way to keep constant contact force. However, the existing on-line stiffness estimation methods cannot guarantee that the environment stiffness estimation converges to the real value when the original position of the part (i.e. environment) is unknown. In addition, although the off-line strategy can accurately identify the environment stiffness, the process of force/deformation data acquisition is complex and time-consuming. Therefore, a sim2real transferring method is proposed to accurately estimate the environmental stiffness. Firstly, the stiffness values of different positions of parts are obtained by finite element simulation analysis, and the simulation environment stiffness library of parts with different materials and shapes is obtained by domain randomization algorithm. Then, the neural network is used to learn the stiffness data in the simulation environment, and the stiffness values of different kinds of parts in the real environment are predicted according to the results. The proposed method overcomes the difficulty that the environmental stiffness and original position cannot be accurately estimated online at the same time. Moreover, it is simpler and more efficient than the off-line identification strategy. The linear motion platform and cantilever beam are used to carry out the experimental verification. The results show that the proposed method can accurately estimate the environmental stiffness, and the estimation error is less than 10%, and the force tracking error based on the estimated stiffness is less than ±0.5 N, which are better than the existing Lyapunov based estimation method.

Key words: thin-walled parts, constant force machining, stiffness estimation, sim2real

CLC Number:

TP273

CHEN Pengfei, LI Xiangfei, HE Xianming, CAI Yuanhao, ZHAO Huan, DING Han. Research on Force Control Based on Sim2Real Transfer for Stiffness of Thin-walled Parts[J]. Journal of Mechanical Engineering, 2021, 57(17): 53-63.

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