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The Frontiers of Iterative Learning Control

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Iterative Learning Control

Abstract

In this chapter we first investigate existing problems and limitations of present iterative learning control (ILC) methods. Consequently we point out the frontiers of ILC research — some are under exploitation whereas others are still virgin lands to ILC. The main purpose of this chapter is to indicate some future research directions by referring to other existing control methods. It is our hope that ILC research can be further diversified and move into all control and application fields. This chapter mainly discusses ILC frontiers from the task and system levels. We will also briefly address other important issues associated with ILC such as implementation, intelligence, design and applications, which will be further detailed in other chapters of this book.

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References

  • Amann, N., Owens, D. H., and Rogers, E. (1994). Non-minimum phase plants in iterative learning control. In Proc. of the IEE Conf. on Intelligent Systems Engineering, pages 107–112.

    Google Scholar 

  • Amann, N., Owens, D. H., and Rogers, E. (1996a). Iterative learning control using optimal feedback and feedforward actions. International Journal of Control, 65(2):277–293.

    Article  MathSciNet  MATH  Google Scholar 

  • Amann, N., Owens, D. H., Rogers, E., and Wahl, A. (1996b). An H ∞ approach to linear iterative learning control design. International Journal of Adaptive Control and Signal Processing, 10(6):767–781.

    Article  MathSciNet  MATH  Google Scholar 

  • Arimoto, S. (1985). Mathematical theory of learning with applications to robot control. In Narendra, K., editor, Adaptive and Learning Systems: Theory and Applications, pages 379–388. Yale University, Yale University, New Haven, Connecticut, USA.

    Google Scholar 

  • Bien, W. S., Lee, H. S., Hwang, D. H., and Lee, J. W. (1992). An ilc method using neural networks for robot manipulator. In Proceedings of the 2nd Int. Conference on Fuzzy Logics and Neural Networks, volume 1, pages 739–742, Iizuka, Japan.

    Google Scholar 

  • Bien, Z. and Chyung, D. H. (1980). Optimal control of delay systems with final function condition. International Journal of Control, 32(3):539–560.

    Article  MathSciNet  MATH  Google Scholar 

  • Bien, Z. and Huh, K.M. (1989). High-order iterative learning control algorithm. IEE Proceedings, Part-D, Control Theory and Applications, 136(3):105–112.

    MATH  Google Scholar 

  • Chan, C. W. and Hui, K. (1994). Actuator saturation compensation for self-tuning controllers. International Journal of Control, 59(2):543–560.

    Article  MathSciNet  MATH  Google Scholar 

  • Chang, W. and Suh, I. (1996). Analysis and design of dual-repetitive controllers. In Proceedings of the 35th IEEE Conference on Decision and Control, Kobe, Japan.

    Google Scholar 

  • Chen, B. M. and Weller, S. R. (1998). Mappings of the finite and infinite zero structures and invertibility structures of general linear multivariable systems under the bilinear transformation. Automatica, 34(1):111–124.

    Article  MathSciNet  MATH  Google Scholar 

  • Chen, Y., Xu, J.-X., Lee, T., and Yamamoto, S. (1997). An iterative lerning control in rapid thermal processing. In Proc. the IASTED Int. Conf. on Modeling, Simulation and Optimization (MSO’97), pages 189–92, Singapore.

    Google Scholar 

  • Chen, Y., Xu, J.-X., and Wen, C. (1998). Iterative learning based extraction of aerobomb drag. AIAA: Journal of Spacecraft and Rockets, 35(1):237–240.

    Article  Google Scholar 

  • Cheres, E. and Palmor, Z. (1989). Stabilization of uncertain dynamic systems including state delay. IEEE Trans. on Automatic Control, 34(9): 116–121.

    MathSciNet  Google Scholar 

  • Chien, C.-J. (1997). The sampled-data iterative learning control for nonlinear systems. In Proceedings of the 35th IEEE Conference on Decision and Control, USA.

    Google Scholar 

  • Chien, C.-J. and Liu, J.-S. (1996). P-type iterative learning controller for robust output tracking of nonlinear time-varying systems. International Journal of Control, 64(2):319–334.

    Article  MathSciNet  MATH  Google Scholar 

  • Corless, M. and Leitman, G. (1981). Continuous state feedback guaranteeing uniform ultimate boundedness for uncertain dynamic systems. IEEE Trans. on Automatic Control, 26(5):1139–1144.

    Article  MATH  Google Scholar 

  • Dou, H., Zhou, Z., Sun, M., and Chen, Y. (1996). Robust high-order P-type iterative learning control for a class of uncertain nonlinear systems. In Presented at the 1996 IEEE Int. Conf. on Systems, Man, and Cybernetics, pages 923–928, Beijing.

    Google Scholar 

  • Edwards, J. B. and Owens, D. H. (1974). Stability problems in the control of of linear multipass processes. Proc. IEE, 121(11):1425–1431.

    Google Scholar 

  • Ge, S., Lee, T., and Zhu, G. (1998). Improving regulation of a single-link flexible manipulator with strain feedback. IEEE Trans. on Robotics and Automation, 14(1).

    Google Scholar 

  • Hale, J. K. (1977). Introduction to functional differential equations. Springer-Verlag.

    Google Scholar 

  • Ham, C., Qu, Z. H., and Kaloust, J. H. (1995). Nonlinear learning control for a class of nonlinear systems based on lyapunov’s direct method. In Proc. of American Control Conference, pages 3024–3028, Seattle, Whashinton, USA.

    Google Scholar 

  • Heinzinger, G., Fenwick, D., Paden, B., and Miyazaki, F. (1992). Stability of learning control with disturbances and uncertain initial conditions. IEEE Trans. of Automatic Control, 37(1):110–114.

    Article  MathSciNet  Google Scholar 

  • Hwang, D.-H., Bien, Z., and Oh, S.-R. (1991). Iterative learning control method for discrete-time dynamic systems. IEE Proceedings, Part-D, Control Theory and Applications, 138(2): 139–144.

    MATH  Google Scholar 

  • Jang, T.-J., Choi, C.-H., and Ahn, H.-S. (1995). Iterative learning control in feedback systems. Automatica, 31(2):243–245.

    Article  MathSciNet  MATH  Google Scholar 

  • Kokotovic, P. V. (1992). The joy of feedback: nonlinear and adaptive. IEEE Control System Magazine, 12(1):7–17.

    Google Scholar 

  • Kurek, J. E. and Zaremba, M. B. (1993). Iterative learning control systhesis based on 2-D system theory. IEEE Trans. of Automatic Control, 38(1):121–125.

    Article  MathSciNet  MATH  Google Scholar 

  • Lee, H.-S. and Bien, Z. (1996). Study on robustness of iterative learning control with non-zero initial error. Int. J. of Control, 64(3):345–359.

    Article  MathSciNet  MATH  Google Scholar 

  • Lee, H. S. and Bien, Z. (1997). A note on convergence property of iterative learning controller with respect to sup norm. Automatica, 33(8): 1591–1593.

    Article  MathSciNet  MATH  Google Scholar 

  • Lee, K. H. and Bien, Z. (1991). Initial condition problem of learning control. IEE Proceedings, Part-D, Control Theory and Applications, 138(6):525–528.

    Google Scholar 

  • Liao, T.-L., Fu, L.-C., and Hsu, C.-F. (1990). Adaptive robust tracking of nonlinear systems and with an application to a robotic manipulator. Systems and Control Letters, 15:339–348.

    Article  MathSciNet  MATH  Google Scholar 

  • Lucibello, P. (1994). State steering by learning for a class of nonlinear control systems. Automatica, 30(9): 1463–1468.

    Article  MathSciNet  MATH  Google Scholar 

  • Lucibello, P., Panzier, S., and Ulivi, G. (1997). Repositioning control of a two-link flexible arm by learning. Automatica, 33(4):579–590.

    Article  MathSciNet  MATH  Google Scholar 

  • Marino, R. and Tornei, P. (1995). Nonlinear Control Design. Prentice Hall.

    Google Scholar 

  • Moore, K. L. (1998). Iterative learning control — an expository overview. Applied & Computational Controls, Signal Processing, and Circuits, To appear. (Available at http://shuya.ml.org:888/~yqchen/ILC/ Ilcrep.zip.gz):1–42.

    Google Scholar 

  • Nakano, M., Inoue, T., Yamamoto, Y., and Hara, S. (1989). Repetitive control. SICE.

    Google Scholar 

  • Oh, S., Bien, Z., and Suh, I. (1988). An iterative learning control method with application for the robot manipulator. IEEE J. of Robotics and Automation, 4(5):508–514.

    Article  Google Scholar 

  • Rogers, E. and Owens, D. (1996). Lyapunov stability theory and performance bounds for a class of 2D linear systems. Multidimensional Systems and Signal Processing, 7:179–194.

    Article  MathSciNet  MATH  Google Scholar 

  • Roh, C. L., Lee, M. N., and Chung, M. J. (1996). ILC for non-minimum phase systems. International Journal of Systems Science, 27(4):419–424.

    Article  MATH  Google Scholar 

  • Saab, S., Vogt, W., and Mickle, M. (1997). Learning control algorithms for tracking slowly varying trajectories. IEEE Transactions on Systems, Man, and Cybernetics — Part B: Cybernetics, 27(4):657–670.

    Article  Google Scholar 

  • Saab, S. S. (1995). A discrete-time learning control algorithm for a class of linear time-invariant systems. IEEE Trans. of Automatic Control, 40(6): 1138–1141.

    Article  MathSciNet  MATH  Google Scholar 

  • Sogo, T. and Adachi, N. (1996). Convergence rates and robustness of iterative learning control. In Proceedings of the 35th IEEE Conference on Decision and Control, volume 3, pages 3050–3055, Kobe, Japan.

    Google Scholar 

  • Wang, J. D., Lee, T. L., and Juang, Y. T. (1996). New methods to design an integral variable structure controller. IEEE Trans. on Automatic Control, 41(1):140–143.

    Article  MathSciNet  MATH  Google Scholar 

  • Wu, H. and Mizukami, K. (1996). Linear and nonlinear stabilizing continuous controllers of uncertain dynamical systems including state delay. IEEE Trans. on Automatic Control, 41(1): 116–121.

    Article  MathSciNet  MATH  Google Scholar 

  • Xu, J.-X. (1997a). Analysis of iterative learning control for a class of nonlinear discrete-time systems. Automatica, 33(10): 1905–1907.

    Article  MathSciNet  MATH  Google Scholar 

  • Xu, J.-X. (1997b). Direct learning of control effors for trajectories with different magnitude scales. Automatica, 33(11).

    Google Scholar 

  • Xu, J.-X. (1998). Direct learning of control effors for trajectories with different time scales. IEEE Transactions on Automatic Control, 43(In Press).

    Google Scholar 

  • Xu, J.-X., Chen, Y., Lee, T., and Yamamoto, S. (1997a). Terminal iterative learning control with an application to RTPCVD thickness control. Automatica, page submitted.

    Google Scholar 

  • Xu, J.-X., Dote, Y., Wang, X., and Shun, B. (1995). On the instability of iterative learning control due to sampling delay. In Proceedings of the 1995 IEEE IECON: 31st International Conference on Industrial Electronics, Control, and Instrumentation, volume 1, pages 150–155, Orlando, FL.

    Google Scholar 

  • Xu, J.-X., Lee, T. H., and He, C. (1997b). Synthesized switching surface design using frequency shaping and terminal attractor with application to flexible joint manipulators. In Proceedings of the 2nd Asian Control Conference, Seoul, Korea.

    Google Scholar 

  • Xu, J.-X., Lee, T. H., and Jia, Q.-W. (1998). Design and analysis of a new adaptive robust control scheme. International Journal of System Science, 29(In press).

    Google Scholar 

  • Xu, J.-X. and Qu, Z. (1996). Robust learning control for a class of non-linear systems. In Proceedings of the 35th IEEE Conference on Decision and Control, Kobe, Japan.

    Google Scholar 

  • Xu, J.-X. and Qu, Z. H. (1998). Robust iterative learning control for a class of nonlinear systems. Automatica, 34(8):In Press.

    Google Scholar 

  • Young, K. K. D. (1993). Variable structure control for robotics and aerospace applications. Elsevier.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore, 119260

    Jian-Xin Xu

  2. Dept. of Electrical Engineering, Korea Advanced Institute of Science and Technology, Kaist, Korea

    Zenn Z. Bien

Authors
  1. Jian-Xin Xu
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  2. Zenn Z. Bien
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Korea

    Zeungnam Bien

  2. Department of Electrical Engineering, National University of Singapore, Singapore

    Jian-Xin Xu

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© 1998 Springer Science+Business Media New York

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Xu, JX., Bien, Z.Z. (1998). The Frontiers of Iterative Learning Control. In: Bien, Z., Xu, JX. (eds) Iterative Learning Control. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5629-9_2

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  • DOI: https://doi.org/10.1007/978-1-4615-5629-9_2

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7575-3

  • Online ISBN: 978-1-4615-5629-9

  • eBook Packages: Springer Book Archive

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