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Robustness of iterative learning control - algorithms with experimental benchmarking

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Języki publikacji
EN
Abstrakty
EN
Iterative learning control is a technique especially developed for application to processes which are required to repeat the same operation over a finite duration. The exact sequence of operation is that the task is completed, the process is reset and then the operation is repeated. Applications are widespread among many industries, e.g. a gantry robot which is required to place items on a conveyor under synchronization as part of a food manufacturing process. In effect, iterative learning control exploits the fact that once a single execution of the task is complete then the input control action and output response produced are available to update the control input for the next trial and thereby sequentially improve performance. Moreover, it may be possible to undertake the required computations during the time between completing one trial and the start of the next. This paper gives an overview of some very significant recent progress in this general area, including results from experimental benchmarking, and also some areas for on-going/future research are outlined.
Rocznik
Strony
205--215
Opis fizyczny
Bibliogr. 14 poz., rys., tab.
Twórcy
autor
  • School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK, etar@ecs.soton.ac.uk
Bibliografia
  • [1] S. Arimoto, S. Kawamura, and F. Miyazaki, "Bettering operations of robots by learning", J. Robotic Systems 1, 123-140 (1984).
  • [2] K.L. Moore, Iterative Learning Control for Deterministic Systems, Advances in Industrial Control Series, Springer Verlag, London, 1993.
  • [3] H.-S. Ahn, Ch. YanQuan, and K.L. Moore, "Iterative learning control: brief survey and categorization", IEEE Transactions on Systems, Man and Cyberneitcs Part C 37(6), 1099-1121 (2007).
  • [4] A. Bristow, M. Tharayil, and A.A. Alleyne, "A survey of iterative learning control", IEEE Control Systems Magazine 26(3), 96-114 (2006).
  • [5] D.H. Owens, N. Amann, E. Rogers, and M. French, "Analysis of iterative learning control schemes - a 2D systems/repetitive processes approach", Multidimensional Systems and Signal Processing 11 (1/2), 125-1777 (2000).
  • [6] N. Amann, D.H. Owens, and E. Rogers, "Predictive optimal iterative learning control", Int. J. Control 69(2), 203-226 ( 1998).
  • [7] J-X. Xu and Y. Tan, "Robust optimal design and convergence properties analysis of iterative learning control approaches", Automatica 1867-1880 (2002).
  • [8] J.D. Ratcliffe, Iterative Learning Control Implemented on a Multi-axis System, PhD Thesis, University of Southampton, UK, 2005.
  • [9] J.D. Ratcliffe, P.L. Lewin, E. Rogers, J.J. Hatonen, and D.H. Owens, "Norm-optimal iterative learning control applied to a gantry robots for automation applications", IEEE Transactions on Robotics 22(6), 1303-1307 (2006).
  • [10] J.D. Ratcliffe, J.J. Hatonen, P.L. Lewin, E. Rogers, and D.H. Owens, "Robustness analysis of an ad joint optimal iterative learning controller with experimental verification", Int. J. Robust and Nonlinear Control, 18(10), 1089-113 (2008).
  • [11] K. Furuta and M. Yamakita, "The design of learning control systems for multivariable systems", Proc. IEEE Int. Symposium on Intelligent Control, 371-376 (1987).
  • [12] C.A. Desoer and M. Vidyasagar, Feedback Systems: Input Output Properties, Academic Press, London, 1975.
  • [13] J.J. Hatonen and D.H. Owens, "New connections between positivity and parameter-optimal iterative learning control", Proc. IEEE International Symposium on Intelligent Control, 69-74 (2003).
  • [14] R.W. Longman, "Iterative learning control and repetitive control for engineering practice", Int. J. Control 73(10), 930-954 (2000).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPG5-0034-0007
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