Improving the Accuracy of Dynamic Model Identification for Moving Industrial Robots Using Indirect Z-Direction Vibration Analysis

With the growing use of industrial robots in high-force operations, accurate dynamic modelling has become increasingly critical for their design and control. The authors previously proposed a novel automated method to identify joint dynamic parameters of moving industrial robots, considering frictional behavior across a large portion of the workspace. This method excites the robot using a “fast chirp” centrifugal force, allowing precise control of the excitation force. However, its accuracy is limited due to the neglect of out-of-plane z-dynamics and the error in the input force model. This paper addresses these limitations to enhance the model’s prediction accuracy. Theoretical and experimental excitation forces are compared to assess their influence on identification. The indirect z-direction vibration response is formulated accounting for the cross-couplings and analyzed to enhance the prediction accuracy of out-of-plane z-dynamics. The experimental results show that the proposed approach reduces prediction error by up to 49.8% compared to the previously identified model, in which the z-direction vibration responses were not considered.