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2008 | 18 | 3 | 279-293
Tytuł artykułu

Iterative Learning Control - monotonicity and optimization

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The area if Iterative Learning Control (ILC) has great potential for applications to systems with a naturally repetitive action where the transfer of data from repetition (trial or iteration) can lead to substantial improvements in tracking performance. There are several serious issues arising from the "2D" structure of ILC and a number of new problems requiring new ways of thinking and design. This paper introduces some of these issues from the point of view of the research group at Sheffield University and concentrates on linear systems and the potential for the use of optimization methods and switching strategies to achieve effective control.
Rocznik
Tom
18
Numer
3
Strony
279-293
Opis fizyczny
Daty
wydano
2008
otrzymano
2007-06-25
poprawiono
2007-07-30
Twórcy
  • Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK
autor
  • Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK
Bibliografia
  • Amann N., Owens D.H. and Rogers E. (1998). Predictive Optimal Iterative Learning Control, International Journal of Control 69(2), 203-226.
  • Arimoto S., Kawamura S. and Miyazaki F. (1984). Bettering operations of robots by learning, Journal of Robotic Systems 1: 123-140.
  • Bien Z. and Xu J. (1998). Iterative Learning Control: Analysis, Integration, and Application, Kluwer.
  • Amann N., Owens D.H. and Rogers E. (1996). Iterative learning control for discrete-time systems with exponential rate of convergence, IEE Proceedings: Control Theory and Applications 143: 217-244.
  • Amann N. (1996). Optimal Algorithms for Iterative Learning Control, Ph. D. thesis, University of Exeter.
  • Camacho E.F and Bordons C. (1998). Model Predictive Control, Springer.
  • Chen Y. and Wen C. (1999). Iterative Learning Control: Robustness and Applications, Springer.
  • Chen Y. and Moore K.L. (2000). Comments on United States Patent 3,555,252 - Learning control of actuators in control systems, Proceedings of the 2000 International Conference on Automation, Robotics, and Control, Singapore.
  • Cryer B.W., Nawrocki P.E. and Lund R.A. (1976). A road simulation system for heavy duty vehicles, Technical report 760361, Society of Automotive Engineers.
  • Daley S., Hätönen J. and Owens D.H. (2004). Hydraulic servo system command shaping using iterative learning control, Proceedings of the Control Conference 2004, Bath, UK.
  • de Roover D. (1997). Motion Control of a Wafer Stage - A Design Approach for Speeding Up IC Production, Ph. D. thesis, Delft University of Technology.
  • Edwards J. B. and Owens D.H. (1982). Analysis and Control of Multipass Processes, Research Studies Press.
  • Furuta K. and Yamakita M. (1987). The design of learning control systems for multivariable systems, Proceedings of the IEEE International Symposium on Intelligent Control, Philadelphia, PA, USA, pp. 371-376.
  • Gorinevsky D. M. (1992). Direct learning of feedforward control for manipulator path tracking, Proceedings of the IEEE International Symposium on Intelligent Control, Glasgow, UK.
  • Gunnarsson S. and Norrlöf M. (2001). On the design of ILC algorithms using optimisation, Automatica 37: 2011-2016.
  • Harte T.J., Hätönen J.J. and Owens D.H. (2005). Discretetime inverse model-based iterative learning control: Stability, monotonicity and robustness, International Journal of Control 78(8), 577-586.
  • Hatzikos V., Hätönen J. and Owens D.H. (2004). Genetic algorithms in norm-optimal and non-linear iterative learning control, International Journal of Control 77(2): 188-197.
  • Hätönen J. (2004). Issues of Algebra and Optimality in Iterative Learning Control, Ph. D. thesis, University of Oulu.
  • Hätönen J. and Owens D.H. (2004). Convex modifications to an iterative learning control law, Automatica 40: 1213-1220.
  • Hätönen J., Harte T.J., Owens D.H., Ratcliffe J., Lewin P. and Rogers E. (2003). A new robust iterative learning control law for application on a gantry robot, Proceedings of the 9th IEEE Conference on Emerging Technologies and Factory Automation, Lisbon, Portugal.
  • Hätönen J.J., Owens D.H. and Moore K.L. (2004). An algebraic approach to iterative learning control, International Journal of Control 77(1), 45-54.
  • Hätönen J.J., Owens D.H. and Feng K. (2006). Basis functions and parameter optimization in high order iterative learning control, Automatica 42(2): 287-294.
  • Lee J.J. and Lee J.W. (1993). Design of Iterative Learning Controller with VCR servo system, IEEE Transactions on Consumer Electronics 39: 13-24.
  • Lee K.S., Bang S.H., Yi S. and Yoon S.C. (1996a). Iterative learning control of heat up phase for a batch polymerization reactor, Journal of Process Control 6(4): 255-262.
  • Lee K.S., Kim W.C. and Lee J.H. (1996b). Model-based Iterative learning control with quadratic criterion for linear batch processes, Journal of Control, Automation and Systems Engineering 3: 148-157.
  • Longman R. W. (2000). Iterative Learning Control and Repetitive Control for engineering practise, International Journal of Control 73(10): 930-954.
  • Moore K.L. (1993). Iterative Learning Control for Deterministic Systems, Springer.
  • Moore K.L. (1998). Multi-loop control approach to designing Iterative Learning Controllers, Proceedings of the 37th IEEE Conference on Decision and Control, Tampa, FL, USA.
  • Norrlöf M. (2000). Iterative Learning Control: Analysis, Design, and Experiments, Ph. D. thesis, Linköping University.
  • Norrlöf Mikael (2002). An adaptive iterative learning control algorithm with experiments on an industrial robot, IEEE Transactions on Robotics and Automation 18(2): 245-251.
  • Owens D.H. and Feng K. (2003). Parameter optimization in Iterative learning control, International Journal of Control 76(11): 1059-1069.
  • Owens D.H., Tomas-Rodriguez M. and Daley S. (2008). Limit sets and switching strategies in parameter optimal iterative learning control, International Journal of Control 81(4): 626-640.
  • Ratcliffe J., Harte T.J., Hätönen J., Lewin P.Rogers E. and Owens D.H. (2004). Practical implementation of a model inverse optimal iterative learning controller on a gantry robot, Proceedings of the IFAC Workshop on Periodic Systems (PSYCO 04), Yokohama, Japan.
  • Rogers E. and Owens D.H. (1992). Stability Analysis for Linear Repetitive Processes, Springer.
  • Tao K. M., Kosut R. L. and Aral G. (1994). Learning feedforward control, Proceedings of the American Control Conference, Baltimore, MD, USA.
  • Togai M. and O. Yamano (1985). Analysis and design of an optimal learning control scheme for industrial robots: A discrete system approach, Proceedings 24th IEEE Conference on Decision and Control, Ft. Lauderdale, FL, USA.
  • Uchiyama M. (1978). Formation of high speed motion pattern of mechanical arm by trial, Transactions of the Society of Instrumentation and Control Engineers 19(5): 706-712.
  • Xu J.X. and Tan Y. (2003). Linear and Nonlinear Iterative Learning Control, Springer.
  • Zilouchian A. (1994). An iterative learning control technique for a dual arm robotic system, Proceedings of the 1994 IEEE International Conference on Robotics and Automation, San Diego, CA, USA, pp. 1528-1533.
Typ dokumentu
Bibliografia
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Identyfikator YADDA
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