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<p>Magnetic levitation systems (MLS) are inherently nonlinear and open-loop unstable, presenting significant challenges for precision control under real-world uncertainties. This paper proposes a novel control framework that integrates feedback linearization control (FLC) with a linear extended state observer (LESO) and a hybrid tuning strategy based on a modified flood algorithm (FA). The original FA is enhanced to reduce computational complexity and enable efficient online tuning of LESO gains adaptively in an event-triggered manner while maintaining offline optimization for FLC parameters. The resulting LESO-FLC controller eliminates the need for exact system models by estimating lumped disturbances and parametric uncertainties in real-time. A short-window cost balances tracking accuracy, control effort, and residual disturbance estimates, while clamping keeps gains within safe bounds. Formal stability analysis using Lyapunov methods confirms the closed-loop stability of the proposed scheme. Extensive simulation results demonstrate the effectiveness of the LESO-FLC controller in tracking various reference trajectories (sine, step, and square), outperforming conventional PID, LQR, and standalone FLC controllers in terms of tracking accuracy, control effort, and robustness to external disturbances and variations in parameters <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\pm 10\%\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>±</mo> <mn>10</mn> <mo>%</mo> </mrow> </math></EquationSource> </InlineEquation>. The proposed method meets the submillimeter precision requirements of industrial-grade MLS applications, making it a scalable solution for real-time control of nonlinear electromechanical systems. While PID and FLC maintain errors within a ±4mm band under nominal conditions, only the LESO-FLC consistently keeps the error below 1mm required for high-precision applications and remains stable under ±10% parameter perturbations and external disturbances. Although this work focuses on MLS, the proposed LESO-FLC framework shows promise for use in other nonlinear and unstable systems where accurate system modeling is difficult and robustness to disturbances is vital, such as robotic manipulators and aerospace control systems with suitable tuning.</p>

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Robust control of a magnetic levitation system via LESO-based feedback linearization tuned by modified flood algorithm

  • 期刊论文

  • 发表日期：

    2025年11月27日

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  • Omar Y. Ismael,
  • Yazen Hudhaifa Shakir Alnema,
  • Akram H. Hameed,
  • Amjad Jaleel Humaidi

摘要

Magnetic levitation systems (MLS) are inherently nonlinear and open-loop unstable, presenting significant challenges for precision control under real-world uncertainties. This paper proposes a novel control framework that integrates feedback linearization control (FLC) with a linear extended state observer (LESO) and a hybrid tuning strategy based on a modified flood algorithm (FA). The original FA is enhanced to reduce computational complexity and enable efficient online tuning of LESO gains adaptively in an event-triggered manner while maintaining offline optimization for FLC parameters. The resulting LESO-FLC controller eliminates the need for exact system models by estimating lumped disturbances and parametric uncertainties in real-time. A short-window cost balances tracking accuracy, control effort, and residual disturbance estimates, while clamping keeps gains within safe bounds. Formal stability analysis using Lyapunov methods confirms the closed-loop stability of the proposed scheme. Extensive simulation results demonstrate the effectiveness of the LESO-FLC controller in tracking various reference trajectories (sine, step, and square), outperforming conventional PID, LQR, and standalone FLC controllers in terms of tracking accuracy, control effort, and robustness to external disturbances and variations in parameters \(\pm 10\%\) ± 10 % . The proposed method meets the submillimeter precision requirements of industrial-grade MLS applications, making it a scalable solution for real-time control of nonlinear electromechanical systems. While PID and FLC maintain errors within a ±4mm band under nominal conditions, only the LESO-FLC consistently keeps the error below 1mm required for high-precision applications and remains stable under ±10% parameter perturbations and external disturbances. Although this work focuses on MLS, the proposed LESO-FLC framework shows promise for use in other nonlinear and unstable systems where accurate system modeling is difficult and robustness to disturbances is vital, such as robotic manipulators and aerospace control systems with suitable tuning.