International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지

Nanoscale Dynamics, Stochastic Modeling, and Multivariable Control of a Planar Magnetic Levitator

  • Kim, Won-Jong (Department of Mechanical Engineering, Texas A&M University)
  • Published : 2003.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents a high-precision magnetically levitated (maglev) stage to meet demanding motion specifications in the next-generation precision manufacturing and nanotechnology. Characterization of dynamic behaviors of such a motion stage is a crucial task. In this paper, we address the issues related to the stochastic modeling of the stage including transfer function identification, and noise/disturbance analysis and prediction. Provided are test results on precision dynamics, such as fine settling, effect of optical table oscillation, and position ripple. To deal with the dynamic coupling in the platen, we designed and implemented a multivariable linear quadratic regulator, and performed time-optimal control. We demonstrated how the performance of the current maglev stage can be improved with these analyses and experimental results. The maglev stage operates with positioning noise of 5 nm rms in $\chi$ and y, acceleration capabilities in excess of 2g(20 $m/s^2$), and closed-loop crossover frequency of 100 Hz.

Keywords

References

  1. Precision Engineering v.22 no.2 High-precision magnetic levitation stage for photolithography W.-J. Kim;D. L. Trumper https://doi.org/10.1016/S0141-6359(98)00009-9
  2. PD. D. Thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology High-Precision Planar Magnetic Levitation W.-J. Kim
  3. IEEE Trans. on Industry Applications v.3 no.2 Design and analysis framework for linear permanentmagnet machines D. L. Trumper;W.-J. Kim;M. E. Williams
  4. IEEE Trans. on Automatic Control v.30 no.6 Minimum-time control of robotic manipulators with geometric path constraints K. G. Shin;N. D. McKay https://doi.org/10.1109/TAC.1985.1104009
  5. IEEE Trans. on Robotics and Automation v.5 no.1 Improving the efficiency of time-optimal path-following algorithms J.-J. E. Slotine;H. S. Yang https://doi.org/10.1109/70.88024
  6. Linear Optimal Control B. D. O. Anderson;J. B. Moore
  7. Nuclear Instruments and Methods v.169 no.1 Design of permanent multipole magnets with oriented rare earth cobalt material K. Halbach https://doi.org/10.1016/0029-554X(80)90094-4
  8. Stochastic Models, Estimation, and Control P. S. Maybeck
  9. Theory and Practice of Recursive Identification L. Ljung;T. Soderstrom
  10. Master's Thesis, Massachusetts Institute of Technology Modeling and Control of a Six Degree of Freedom Magnetic/Fluidic Motion Control Stage S. J. Ludwick
  11. Synchronous Motor and Converters A. Blondel
  12. Transactions AIEE v.48 no.3 Two-reaction theory of synchronous machines, generalized method of analysis-Part I R. H. Park
  13. Classical Mechanics H. Goldstein
  14. Control Systems Toolbox for Use with MATLAB Mathworks, Inc.
  15. Proc. of the Automatic Control Conference Adaptive proximate time-optimal control: Continuous time case M. L. Workman;R. L. Kosut;G. F. Franklin