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A study on iterative learning control for vibration of Stewart platform

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  • Control Theory and Applications
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Abstract

This paper presents the replication of a desired vibration response by iterative learning control system for a Stewart platform. The Stewart platform is a multi-input, multi-output system with parameter uncertainties including system nonlinearity and joint nonlinearity. Most vehicle manufacturers are relying on road test simulation facilities in order to reduce development time and to enhance product quality. Road simulation algorithm is essential for developing road test simulation system. With digital signal processing technology, more complex control algorithms including iterative learning control can be utilized. In this paper, a controller based on iterative learning control (ILC) algorithm was developed to produce the desired target response in case of a single actuator as the first experiment after programmed with C language. As a next experiment, the control algorithm was implemented in a road test simulation system using a Stewart platform. A real test was carried out to replicate total six channels of acceleration signals measured at top and left side points of audio player system installed to a car running on Belgian road. The convergence rate and test simulation accuracy higher than 90% showed that the algorithm was acceptable to replicate the target vibration response.

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References

  1. R. Longman, M. Phan, and J. Juang, “An overview of a sequence of research developments in learning and repetitive control,” Proceedings of the 1st International Conference on Motion and Vibration Control. Yokohama, Japan, 1992.

    Google Scholar 

  2. R. Longman, C. Chang, and M. Phan, “Discrete time learning control in nonlinear systems,” Proceedings of the 1992 AIAA/AAS Astrodynamics Conference, Hilton Head, South Carolina, pp. 501–511, 1992.

    Google Scholar 

  3. R. Longman, “Iterative learning control and repetitive control for engineering practice,” International Journal of Control, vol. 73, no. 10, pp. 930–954, 2000.

    Article  MathSciNet  MATH  Google Scholar 

  4. Q. Xu, X. Li, and M. Lv, “Adaptive ILC for Tracking Nonrepetitive Reference Trajectory of 2-D FMM under Random Boundary Condition,” International Journal of Control, Automation and Systems, vol. 14, no. 2, pp. 478–485, April 2016. [click]

    Article  Google Scholar 

  5. T. Xiao, X. Li, and J. Ho, “An adaptive discrete-time ILC strategy using fuzzy systems for iteration-varying reference trajectory tracking,” International Journal of Control, Automation and Systems, vol. 13, no. 1, pp. 222–230, February 2015. [click]

    Article  Google Scholar 

  6. T. Doh, J. Ryoo, and D. Chang, “Robust iterative learning controller design using the performance weighting function of feedback control systems,” International Journal of Control, Automation and Systems, vol. 12, no. 1, pp. 63–70, February 2014.

    Article  Google Scholar 

  7. J. M. Pak, C. K. Ahn, Y. S. Shmaliy, P. Shi, and M. T. Lim, “Switching extensible FIR filter bank for adaptive horizon state estimation with application,” IEEE Transactions on Control Systems Technology, vol. 24, no. 3, pp. 1052–1058, May 2016.

    Article  Google Scholar 

  8. J. M. Pak, C. K. Ahn, Y. S. Shmaliy, and M. T. Lim, “Improving reliability of particle filter-based localization in wireless sensor networks via hybrid particle/FIR filtering,” IEEE Transactions on Industrial Informatics, vol. 11, no. 5, pp. 1089–1098, Oct. 2015.

    Article  Google Scholar 

  9. J. M. Pak, C. K. Ahn, P. Shi, Y. S. Shmaliy, and M. T. Lim. “Distributed hybrid particle/FIR filtering for mitigating NLOS effects in TOA-based localization using wireless sensor networks,” IEEE Transactions on Industrial Electronics (In press, DOI: 10.1109/TIE.2016.2608897), 2017.

    Google Scholar 

  10. J. M. Pak, C. K. Ahn, Y. S. Shmaliy, P. Shi, and M. T. Lim. “Accurate and reliable human localization using composite particle/FIR filtering,” IEEE Transactions on Human-Machine Systems (In press, DOI: 10.1109/THMS.2016.2611826), 2017.

    Google Scholar 

  11. Q. Zhou, H. Li, C. Wu, L. Wang, and C. K. Ahn. “Adaptive fuzzy control of nonlinear systems with unmodeled dynamics and input saturation using small-gain approach,” IEEE Transactions on Systems, Man and Cybernetics (In press, DOI:10.1109/TSMC.2016.2586108), 2016

    Google Scholar 

  12. C. K. Ahn, P. Shi, and M. V. Basin. “Two-dimensional dissipative control and filtering for roesser model,” IEEE Transactions on Automatic Control, vol. 60, no. 7, pp. 1745–1759, July 2015.

    Article  MathSciNet  Google Scholar 

  13. C. K. Ahn, L. Wu, and P. Shi. “Stochastic stability analysis for 2-D roesser systems with multiplicative noise,” Automatica, vol. 69, pp. 356–363, July 2016. [click]

    Article  MathSciNet  MATH  Google Scholar 

  14. C. K. Ahn, P. Shi, and M. V. Basin. “Deadbeat dissipative FIR filtering,” IEEE Transactions on Circuits and Systems I, vol. 63, no. 8, pp 1210–1221, August 2016.

    Article  MathSciNet  Google Scholar 

  15. B. Cryer, P. Nawrocki, and R. Lund, “Road simulation system for heavy duty vehicles,” SAE Technical Paper 760361, DOI:10.4271/760361, 1976.

    Google Scholar 

  16. S. Arimoto, S. Kawamura, and F. Miyazaki, “Bettering operation of robots by learning,” Journal of Robotic System, vol. 1, no. 2, pp. 123–140, 1984. [click]

    Article  Google Scholar 

  17. H. Abdellatif, and B. Heimann, “Advanced model-based control of a 6-DOF hexapod robot: A case study,” IEEE/ASME Transactions on Mechatronics, vol. 15, no. 2, pp. 269–279. 2010.

    Article  Google Scholar 

  18. N. Amann, D. Owens, and E. Rogers, “Iterative learning control using optimal feedback and feedforward actions,” International Journal of Control vol. 65, no. 2, pp. 277–293, 1996. [click]

    Article  MathSciNet  MATH  Google Scholar 

  19. N. Amann, D. Owens, E. Rogers, and A. Wahl, “An H ∞ approach to linear iterative learning control design,” International Journal of Adaptive Control and Signal Processing, vol. 10, no. 6, pp. 767–781, 1996. [click]

    Article  MathSciNet  MATH  Google Scholar 

  20. K. Barton, S. Mishira, and E. Xargay, “Robust iterative learning control: L 1 adaptive feedback control in an ILC framework,” Proc. of American Control Conference, San Francisco, CA, USA, pp. 3663–3668, 2011.

    Google Scholar 

  21. Z. Bien, and K. M. Huh, “High-order iterative learning control algorithm,” IET Control Theory & Applications, vol. 136, no. 3, pp. 105–112, 1989.

    Article  MATH  Google Scholar 

  22. J. Cuyper, M. Verhaegen, and J. Swerves, “Off-line feedforward and feedback control on a vibration rig,” Control Engineering Practice, vol. 11, no. 2, pp. 129–140, February 2003.

    Article  Google Scholar 

  23. A. Johansson, Dynamic Response Reconstruction using Passive Components, Chalmers University of Technology Gothenburg, Sweden, Ph.D. dissertation, 2012.

    Google Scholar 

  24. D. Lee, Y. Park, Y. Park, H. Kim, and J. Park, “Iterative feed-forward control of shaking table system based on FRF of hydraulic actuator,” Proc. of 12th Asia-Pacific Vibration Conference, Sapporo, Japan, pp. 1–7, 2007.

    Google Scholar 

  25. G. Shen, Z. Ye, D. Cong, and J. Han, “Implementation of electrohydraulic shaking table controllers with a combined adaptive inverse control and minimal control synthesis algorithm,” IET Control Theory & Application, vol. 5, no. 13, pp. 1471–1483, 2011.

    Article  MathSciNet  Google Scholar 

  26. P. Xu, G. Peticca, and D. Wong, “A technique for developing a high accuracy durability test for a light truck on a six degree-of-freedom road test simulator,” International Journal of Vehicle Design, vol. 47, no. 1–4, pp. 290–304, 2008.

    Article  Google Scholar 

  27. C. Freeman, P. Lewin, E. Rogers, and J. Ratcliffe, “Iterative learning control applied to a gantry robot and conveyor system,” Transactions of the Institute of Measurement and Control, vol. 32, no. 3, pp. 251–264, 2010.

    Article  Google Scholar 

  28. Instron Structural Testing Systems: RS TWR Manual, 2013.

  29. MTS Co., Ltd.: RPC Pro Software Manual, 2013

  30. Spectral Dynamics: PUMA Manual, 2013

  31. B. Ko and S. Kang, “Replication of automotive vibration target signal using iterative learning control and Stewart platform with Halbach magnet array,” Transactions of the KSNVE, vol. 23, no. 5, pp. 438–444, 2013.

    Google Scholar 

  32. J. Wang, W. Geraint, and D. Howe, “A general framework for the analysis and design of tubular linear permanent magnet machines,” IEEE Transaction on Magnetics, vol. 35, no. 3, pp. 1986–2000, May 1999.

    Article  Google Scholar 

  33. J. Wang, G. Jewell, and D. Howe, “Design optimization and comparison of tubular permanent magnet machine topologies,” IEE Proceedings-Electric Power Applications, vol. 148, no. 5, pp. 456–464, September 2001.

    Article  Google Scholar 

  34. C. Astratini-Enache, R. Olaru, and C. Petrescu, “Moving magnet type actuator with ring magnets,” Journal of Electrical Engineering, vol. 61, no. 7/s, pp. 144–147, 2010.

    Google Scholar 

  35. R. Clark, D. Smith, P. Mellor, and D. Howe, “Design optimization of moving-magnet actuators for reciprocating electro-mechanical systems,” IEEE Transactions on Magnetics, vol. 31, no. 6, pp. 3746–3748, November 1995.

    Article  Google Scholar 

  36. K. Halbach, “Design of permanent multipole magnets with oriented rare earth cobalt material,” Nuclear Instrument and Method, vol. 169, no. 1, pp. 1–10, 1980. [click]

    Article  MathSciNet  Google Scholar 

  37. J. Ofori-Tenkorang and J. Lang, “A comparative analysis of torque production in Halbach and conventional surface-mounted permanent-magnet synchronous motors,” Proceedings IEEE IAS 30th Annual meeting, pp. 657–663, 1995.

    Google Scholar 

  38. D. Trumper, M. Williams, and T. Nguyen, “Magnet arrays for synchronous motors,” Proc. of the IEEE Industrial Applications Society Annual Meeting, Toronto, Canada, pp. 9–18, 1993.

    Google Scholar 

  39. D. Trumper, W. Kim, and M. Williams, “Design and analysis framework for linear permanent-magnet machines,” IEEE Transactions of the Industry Applications, vol. 32, no. 2, pp. 371–379, 1996.

    Article  Google Scholar 

  40. D. Stewart, “A platform with six degrees of freedom,” Proceedings of Institute of Mechanical Engineering, vol. 180, no. 1, pp. 371–386, 1965.

    Article  Google Scholar 

  41. K. Serdar, Serial and Parallel Robot Manipulators-Kinematics, Dynamics, Control and Optimization, pp. 167–178, InTechopen.com, 2012.

    Google Scholar 

  42. E. Fletcher, “A Stewart platform based manipulator: general theory and practical construction,” International Journal of Robotics Research, vol. 5, no. 2, pp. 157–182, 1986.

    Article  Google Scholar 

  43. K. Liu, J. Fitzgerald, and F. Lewis, “Kinematic analysis of a Stewart platform manipulator,” IEEE Transactions on Industrial Electronics, vol. 40, no. 2, pp. 282–293, April 1993.

    Article  Google Scholar 

  44. S. Salcudean, P. Drexel, D. Ben-Dov, A. Taylor, and P. Lawrence, “A six degree-of freedom, hydraulic, one person motion simulator,” Proc, of IEEE International Conference on Robotics and Automation, pp. 2437–2443, 1994.

    Google Scholar 

  45. D. Trumper and M. Williams, “Halbach arrays in precision motion control,” The Art and Science of Magnet Design: A Festschrift in honor of Klaus Halbach, vol. 1, pp. 75–84, February 1995.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Inha Technical College, 100 Inha-ro Nam-Gu, Incheon, 402-752, Korea

    Byeongsik Ko & Dong W. Kim

  2. Department of Electronic Engineering, Incheon National University, Incheon, 402-752, Korea

    Jong-Wook Park

Authors
  1. Byeongsik Ko
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  2. Jong-Wook Park
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  3. Dong W. Kim
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Corresponding authors

Correspondence to Jong-Wook Park or Dong W. Kim.

Additional information

Recommended by Associate Editor Choon Ki Ahn under the direction of Editor Myo Taeg Lim. This work was supported by the Incheon National University Research Grant in 2013.

Byeongsik Ko received his B.S. degree in Korea Aeronautical University in 1984. He also received his M.S. degree in KAIST and Ph.D. degree in UC Berkeley. He is currently a faculty of Inha Technical College. His research interests are vehicle NVH, noise, and vibration control.

Jong W. Park received his Ph.D. degree in Electronic Engineering from Inha University in 1985. He is a professor of Incheon National University. He had been the Director of Incheon Technology Innovation Center from 1999 to 2003. His research interests include robotics and motion estimation of robot vision system.

Dong W. Kim received his Ph.D. degree in Electrical Engineering from Korea University in 2007. He is an associate professor of Inha Technical College. His research interests include robotics, advanced robot design, evolutionary multi-mobile robot system, humanoid robot, soft computing and their application to control.

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Ko, B., Park, JW. & Kim, D.W. A study on iterative learning control for vibration of Stewart platform. Int. J. Control Autom. Syst. 15, 258–266 (2017). https://doi.org/10.1007/s12555-016-0665-7

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  • DOI: https://doi.org/10.1007/s12555-016-0665-7

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