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Frequency Domain Auto-tuning of Structured LPV Controllers for High-Precision Motion Control (2403.05878v2)

Published 9 Mar 2024 in eess.SY and cs.SY

Abstract: Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype.

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References (19)
  1. H. Butler, “Position control in lithographic equipment: Applications of control,” IEEE Control Systems Magazine, no. 5, pp. 28–47, 2011.
  2. B. Bukkems, R. van de Molengraft, M. Heemels, N. van de Wouw, and M. Steinbuch, “A piecewise linear approach towards sheet control in a printer paper path,” in Proc. Amer. Control Conf. (ACC), 2006.
  3. T. Qu, J. Chen, S. Shen, Z. Xiao, Z. Yue, and H. Y. Lau, “Motion control of a bio-inspired wire-driven multi-backbone continuum minimally invasive surgical manipulator,” in Proc. of the IEEE International Conference on Robotics and Biomimetics, pp. 1989–1995, 2016.
  4. X. Ye, Y. Zhang, and Y. Sun, “Robotic pick-place of nanowires for electromechanical characterization,” in Proc. of the 2012 IEEE International Conference on Robotics and Automation, pp. 2755–2760, 2012.
  5. T. Oomen, “Advanced motion control for precision mechatronics: control, identification, and learning of complex systems,” IEEJ Journal of Industry Applications, vol. 7, no. 2, pp. 127–140, 2018.
  6. M. Steinbuch, “Design and control of high tech systems,” in Proc. of the IEEE international Conference on Mechatronics, pp. 13–17, 2013.
  7. M. Steinbuch and M. Norg, “Advanced motion control: An industrial perspective,” European Journal of Control, pp. 278–293, 1998.
  8. X.-j. Zhu et al., “A simple auto-tuner in frequency domain,” Computers & chemical engineering, vol. 30, no. 4, pp. 581–586, 2006.
  9. E. van Solingen, J. van Wingerden, and T. Oomen, “Frequency-domain optimization of fixed-structure controllers,” International Journal of Robust and Nonlinear Control, vol. 28, no. 12, pp. 3784–3805, 2018.
  10. C. Hwang and C.-Y. Hsiao, “Solution of a non-convex optimization arising in pi/pid control design,” Automatica, vol. 38, no. 11, pp. 1895–1904, 2002.
  11. H. Panagopoulos, K. Astrom, and T. Hagglund, “Design of pid controllers based on constrained optimization,” in Proc. Amer. Control Conf. (ACC), vol. 6, pp. 3858–3862, IEEE, 1999.
  12. P. Gahinet and P. Apkarian, “Decentralized and fixed-structure H∞subscript𝐻H_{\infty}italic_H start_POSTSUBSCRIPT ∞ end_POSTSUBSCRIPT control in MATLAB,” in 2011 50th IEEE conference on decision and control and european control conference, pp. 8205–8210, IEEE, 2011.
  13. R. Toth, H. S. Abbas, and H. Werner, “On the state-space realization of lpv input-output models: Practical approaches,” IEEE Transactions on Control Systems Technology, vol. 20, no. 1, pp. 139–153, 2012.
  14. W. K. Gawronski, Dynamics and control of structures: A modal approach. Springer Science & Business Media, 2004.
  15. S. Skogestad and I. Postlethwaite, Multivariable feedback control: analysis and design. 2007.
  16. M. Van de Wal, G. van Baars, F. Sperling, and O. Bosgra, “Multivariable H∞subscript𝐻H_{\infty}italic_H start_POSTSUBSCRIPT ∞ end_POSTSUBSCRIPT/μ𝜇\muitalic_μ feedback control design for high-precision wafer stage motion,” Control engineering practice, vol. 10, no. 7, pp. 739–755, 2002.
  17. R. Eberhart and J. Kennedy, “Particle swarm optimization,” in Proc. IEEE Int. Conf. on neural networks, vol. 4, pp. 1942–1948, 1995.
  18. R. Battiti and F. Masulli, “BFGS optimization for faster and automated supervised learning,” in Proc. Int. Neural Network Conf., pp. 757–760, Springer, 1990.
  19. R. Whitbeck and L. Hofmannf, “Digital control law synthesis in the w’domain,” J. of Guid. and Control, vol. 1, no. 5, pp. 319–326, 1978.

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