Variable-parameter-model-based iterative pre-compensation method of the tracking error. (July 2021)

• Record Type: Journal Article
• Authors: Zhang, Dailin; Chen, Huangchao; Wang, Zining; Zhao, Huan; Ding, Han
• Is Part Of: Mechanical systems and signal processing. Volume 156(2021)
• Publication Date: 2021-07
• Subjects: Data-driven -- Pre-compensation -- Tracking error -- Moment-of-inertia -- Servo systems; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.107687
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: A variable-parameter-model-based iterative pre-compensation method of the tracking error is proposed to predict the optimal pre-compensation value when parameters of drive models change. 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. 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. Abstract: 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.