Variable-parameter-model-based iterative pre-compensation method of the tracking error

The iterative pre-compensation method can predict the optimal pre-compensation value and compensate the tracking error effectively, but the compensation effect decreases if parameters of drive systems change. This paper proposes a variable-parameter-model based iterative pre-compensation method of the tracking error, which can predict the optimal pre-compensation value when parameters of drive systems change. The proposed iterative pre-compensation method of the tracking error can be used to compensate the tracking error of any trajectory by using the predicted pre-compensation value. There are three contributions in detail. Firstly, a variable-parameter-model-based iterative pre-compensation method of the tracking error is proposed based on the designed iterative pre-compensation (IPC) model. Secondly, the data-driven pre-compensation method is proposed to obtain the uncertain portion of the pre-compensation value and adapt to the change of the moment-of-inertia. Thirdly, the identification method of the moment-of-inertia is proposed and applied to the data-driven pre-compensation. In the end, experiments were conducted to verify the proposed iterative pre-compensation method and the experimental results show that the variable-parameter-model-based iterative pre-compensation method of the tracking error can reduce the tracking error and adapt to the change of the moment-of-inertia. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This paper presents a variable-parameter-model-based iterative pre-compensation method for tracking error, which can predict the optimal pre-compensation value when parameters of drive systems change. Experimental results demonstrate that this method can reduce tracking error and adapt to changes in moment-of-inertia.