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Neural-network-based adaptive robust precision motion control of linear motors with asymptotic tracking performance

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Abstract

High precision motion control of permanent magnet linear motors (PMLMs) is limited by undesired nonlinear dynamics, parameter variations, and unstructured uncertainties. To tackle these problems, this paper presents a neural-network-based adaptive robust precision motion control scheme for PMLMs. The presented controller contains a robust feedback controller and an adaptive compensator. The robust controller is designed based on the robust integral of the sign of the error method, and the adaptive compensator consists of a neural network component and a parametric component. Moreover, a composite learning law is designed for the parameter adaption in the compensator to further enhance the control performance. Rigorous stability analysis is provided by using the Lyapunov theory, and asymptotic tracking is theoretically achieved. The effectiveness of the proposed method is verified by comparative simulations and experiments on a PMLM-driven motion stage.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This document is the results of the research project funded in part by the National Science and Technology Major Project of China 2017ZX02101007-001, in part by China Postdoctoral Science Foundation (No. 2021TQ0070) and in part by State Key Laboratory of ASIC & System (No. 2021KF007).

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Authors and Affiliations

  1. Shanghai Engineering Research Center of Ultra-Precision Motion Control and Measurement, Academy for Engineering and Technology, Fudan University, Shanghai, 200433, China

    Runze Ding, Chenyang Ding & Xiaofeng Yang

  2. State Key Laboratory of ASIC and System, School of Microelectronic, Fudan University, Shanghai, 200433, China

    Chenyang Ding, Yunlang Xu & Xiaofeng Yang

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  1. Runze Ding
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  2. Chenyang Ding
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  3. Yunlang Xu
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  4. Xiaofeng Yang
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Correspondence to Chenyang Ding.

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Ding, R., Ding, C., Xu, Y. et al. Neural-network-based adaptive robust precision motion control of linear motors with asymptotic tracking performance. Nonlinear Dyn 108, 1339–1356 (2022). https://doi.org/10.1007/s11071-022-07258-0

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