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Reseach Article

Point to Point ILC with Receding Horizon Optimization Approach

by Haris Anwaar, Yin YiXin, Muhammad Ammar Ashraf, Salman Ijaz
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 165 - Number 11
Year of Publication: 2017
Authors: Haris Anwaar, Yin YiXin, Muhammad Ammar Ashraf, Salman Ijaz
10.5120/ijca2017914074

Haris Anwaar, Yin YiXin, Muhammad Ammar Ashraf, Salman Ijaz . Point to Point ILC with Receding Horizon Optimization Approach. International Journal of Computer Applications. 165, 11 ( May 2017), 19-24. DOI=10.5120/ijca2017914074

@article{ 10.5120/ijca2017914074,
author = { Haris Anwaar, Yin YiXin, Muhammad Ammar Ashraf, Salman Ijaz },
title = { Point to Point ILC with Receding Horizon Optimization Approach },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 165 },
number = { 11 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume165/number11/27618-2017914074/ },
doi = { 10.5120/ijca2017914074 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:12:12.935698+05:30
%A Haris Anwaar
%A Yin YiXin
%A Muhammad Ammar Ashraf
%A Salman Ijaz
%T Point to Point ILC with Receding Horizon Optimization Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 165
%N 11
%P 19-24
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Iterative learning control is a control technique used for the tracking of a finite duration trajectory. Iterative learning control (ILC) with focus on speed of tracking specific points and tracking error on these points is analyzed in this paper. A technique is introduced which employs the receding horizon optimization to track the points along with the iterative learning control is introduced. In order to increase the efficiency of optimization, use of Laguerre functions is introduced which gives more freedom in parameterizing the optimization trajectory and in tuning the optimization parameters. Hence the technique can be efficiently used to track points within the trajectory with good performance.

References
  1. C. T. Freeman and Y. Tan, “Iterative learning control with mixed constraints for point-to-point tracking,” IEEE Trans. Control Syst. Technol., vol. 21, no. 3, pp. 604–616, 2013.
  2. H. Ding and J. Wu, “Point-to-point motion control for a high-acceleration positioning table via cascaded learning schemes,” IEEE Trans. Ind. Electron., vol. 54, no. 5, pp. 2735–2744, 2007.
  3. C. Chien and Y. Shu, “Study of a Class of Sampled-Data ILC from the Point of Performance Improvement and Memory Capacity,” Control and Decision Conference (CCDC), Chinese, pp. 4197–4202, 2016.
  4. R. Chi, Z. Hou, B. Huang, and S. Jin, “A Unified Data-driven Design Framework of Optimality-based Generalized Iterative Learning Control,” Comput. Chem. Eng., vol. 77, pp. 10–23, 2015.
  5. R. Chi, Z. Hou, S. Jin, C. J. Chien, and D. Wang, “Terminal ILC design and analysis via a dynamical predictive model,” IEEE Int. Conf. Control Autom. ICCA, vol. 639798, no. 1, pp. 1156–1161, 2014.
  6. J. Xu, Y. Chen, T. H. Lee, and S. Yamamoto, “Terminal iterative learning control with an application to RTPCVD thickness control ଝ,” Automatica, vol. 35, pp. 1535–1542, 1999.
  7. G. Gauthier, M. Ieee, B. Boulet, and S. Member, “Robust Design of Terminal ILC with an Internal Model Control Using μ -analysis and a Genetic Algorithm Approach,” American Control Conference, pp. 2069–2075, 2010.
  8. G. Gauthier and B. Boulet, “Terminal Iterative Learning Control design with singular value decomposition decoupling for thermoforming ovens,” 2009 Am. Control Conf., no. 1, pp. 1640–1645, 2009.
  9. Y. Liu, R. Chi, and Z. Hou, “Terminal ILC for Tracking Iteration-varying Target Points,” Asian Journal of Control, vol. 12, no. June, pp. 266–272, 2015.
  10. K.-H. Park, “A study on the robustness of a PID-type iterative learning controller against initial state error,” Int. J. Syst. Sci., vol. 30, no. 1, pp. 49–59, 1999.
  11. J. Van De Wijdeven and O. Bosgra, “Hankel iterative learning control for residual vibration suppression with MIMO flexible structure experiments,” Proc. Am. Control Conf., vol. 1, pp. 4993–4998, 2007.
  12. C. T. Freeman, “Constrained Point-to-Point Iterative Learning Control,” IFAC Proceedings Volumes, vol. 0, no. 7, pp. 3611–3616, 2011.
  13. L. Wang, C. T. Freeman, and E. Rogers, “Predictive iterative learning control with experimental validation,” Control Eng. Pract., vol. 53, pp. 24–34, 2016.
  14. B. Wahlberg, “System Identification Using Laguerre Models,” IEEE Trans. Automat. Contr., vol. 36, no. 5, pp. 551–562, 1991.
  15. P. M. Van den Hof and O. H. Bosgra, “A Generalized Orthonormal Basis for Linear Dynamical Systems,” IEEE Trans. Automat. Contr., vol. 40, no. 3, pp. 451–465, 1995.
  16. L. Wang, “Discrete model predictive controller design using Laguerre functions,” J. Process Control, vol. 14, no. 2, pp. 131–142, 2004.
  17. H. Ahn, Y. Chen, and K. L. Moore, “Iterative Learning Control : Brief Survey and Categorization,” IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 37, no. 6, pp. 1099–1121, 2007.
  18. D. A. Bristow and M. Tharayil, “A learning-based method for high-performance tracking control,” IEEE Control Systems. June, pp. 96–114, 2006.
  19. C. T. Freeman, “Constrained point-to-point iterative learning control with experimental verification,” Control Eng. Pract., vol. 20, no. 5, pp. 489–498, 2012.
  20. B. Chu, C. T. Freeman, and D. H. Owens, “A Novel Design Framework for Point-to-Point ILC Using Successive Projection,” IEEE Transactions on Control Systems Technology, vol. 23, no. 3, pp. 1156–1163, 2015.
Index Terms

Computer Science
Information Sciences

Keywords

Point to Point Iterative learning control receding horizon control Iterative Learning control