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Lyapunov-Based Controller Using Nonlinear Observer for Planar Motors

Author

Listed:
  • Khac Huan Su

    (Department of Electrical Engineering, Chonnam National University, Gwangju 61186, Korea)

  • Jaeyun Yim

    (Department of Energy System Engineering, Chung-Ang University, Seoul 06974, Korea)

  • Wonhee Kim

    (School of Energy System Engineering, Chung-Ang University, Seoul 06974, Korea)

  • Youngwoo Lee

    (Department of Electrical Engineering, Chonnam National University, Gwangju 61186, Korea)

Abstract

In general, it is not easy work to design controllers and observers for high-order nonlinear systems. Planar motors that are applied to semiconductor wafer-stage processes have 14th-order nonlinear dynamics and require high resolution for position tracking. Thus, many sensors are required to achieve enhanced tracking performance because there are many state variables. To handle these problems, we developed a Lyapunov-based controller to improve the position tracking performance. Consequently, a nonlinear observer (NOB) was also developed to estimate all of the state variables including the position, the velocity, and the phase current using only position feedback. The closed-loop stability is proved through Lyapunov theory and the input-to-state stability (ISS) property. The proposed method was evaluated based on the simulation results and compared with the conventional proportional–integral–derivative (PID) control method to show the improvement in the position tracking performance.

Suggested Citation

  • Khac Huan Su & Jaeyun Yim & Wonhee Kim & Youngwoo Lee, 2022. "Lyapunov-Based Controller Using Nonlinear Observer for Planar Motors," Mathematics, MDPI, vol. 10(13), pages 1-18, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2177-:d:845116
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    References listed on IDEAS

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    1. Zhenhua Cui & Jiyong Dai & Jianrui Sun & Dezhi Li & Licheng Wang & Kai Wang & A. M. Bastos Pereira, 2022. "Hybrid Methods Using Neural Network and Kalman Filter for the State of Charge Estimation of Lithium-Ion Battery," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, May.
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    3. Li, Dezhi & Li, Shuo & Zhang, Shubo & Sun, Jianrui & Wang, Licheng & Wang, Kai, 2022. "Aging state prediction for supercapacitors based on heuristic kalman filter optimization extreme learning machine," Energy, Elsevier, vol. 250(C).
    4. Wonhee Kim & Donghoon Shin & Youngwoo Lee, 2020. "Nonlinear Position Control Using Only Position Feedback under Position Errors and Yaw Constraints for Air Bearing Planar Motors," Mathematics, MDPI, vol. 8(8), pages 1-18, August.
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