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<p>In recent years, with the increasing complexity of controlled systems and the challenges associated with model accuracy, data-driven control methods have attracted growing attention due to their ability to bypass the need for precise system modeling. In response to the nonlinear, time-varying, and model-uncertain characteristics of magnetic suspension vibration isolation systems, this paper investigated a model-free adaptive control method based on compact form dynamic linearization, and its application to magnetic suspension vibration isolation systems. The proposed control method collected input–output data in real-time, solving and updating the pseudo-partial derivatives (PPD) and the required output quantities. A six degree-of-freedom (DOF) magnetic suspension active vibration isolation system was designed and experimentally validated. Experimental results demonstrated that the proposed compact form dynamic linearization based model-free adaptive controller (CFDL-MFAC) performs exceptionally well in addressing the unknown system model problem. Specifically, under a 1&#xa0;Hz low-frequency disturbance, the method achieved an 8.21&#xa0;dB reduction in acceleration, confirming the effectiveness and practicality of the proposed method.</p>

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Compact Form Dynamic Linearization Based Model-Free Adaptive Control for Magnetic Suspension Active Vibration Isolation System

  • 期刊论文

  • 发表日期：

    2025年10月1日

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  • G. Yuan,
  • Q. Wu,
  • Y. Chen,
  • B. Liu

摘要

In recent years, with the increasing complexity of controlled systems and the challenges associated with model accuracy, data-driven control methods have attracted growing attention due to their ability to bypass the need for precise system modeling. In response to the nonlinear, time-varying, and model-uncertain characteristics of magnetic suspension vibration isolation systems, this paper investigated a model-free adaptive control method based on compact form dynamic linearization, and its application to magnetic suspension vibration isolation systems. The proposed control method collected input–output data in real-time, solving and updating the pseudo-partial derivatives (PPD) and the required output quantities. A six degree-of-freedom (DOF) magnetic suspension active vibration isolation system was designed and experimentally validated. Experimental results demonstrated that the proposed compact form dynamic linearization based model-free adaptive controller (CFDL-MFAC) performs exceptionally well in addressing the unknown system model problem. Specifically, under a 1 Hz low-frequency disturbance, the method achieved an 8.21 dB reduction in acceleration, confirming the effectiveness and practicality of the proposed method.