Advertisement

Pseudo-Downsampled ILC

  • Danwei WangEmail author
  • Yongqiang Ye
  • Bin Zhang
Chapter
  • 858 Downloads
Part of the Advances in Industrial Control book series (AIC)

Abstract

In this chapter, two multi-rate iterative learning control (ILC) schemes, pseudo-downsampled ILC and two-mode ILC are proposed for good learning performance. In pseudo-downsampled ILC, error and input signals are downsampled before they are used in ILC learning law. The output of ILC is then upsampled to the original rate for the next cycle. In two-mode ILC, different learning mechanisms are used on low and high frequency bands, respectively. On low frequency band, a conventional ILC with the original sampling rate is used. While on the high frequency band, a pseudo-downsampled ILC is used. Experimental results are presented to demonstrate the effectiveness of the proposed multi-rate ILC schemes.

Keywords

Down-sampling Convergence Robustness Anti-imaging  Anti-aliasing 

References

  1. 1.
    Moore KL (2001) An observation about monotonic convergence of discrete-time, P-type iterative learning control. In: IEEE Symposium on Intelligent Control, Mexico, pp 45–49Google Scholar
  2. 2.
    Hillenbrand S, Pandit M (2000) An iterative learning controller with reduced sampling rate for plant with variations of initial states. Int J Control 73:882–889CrossRefzbMATHMathSciNetGoogle Scholar
  3. 3.
    Sadegh N, Hu A, James C (2002) Synthesis, stability analysis, and experimental implementation of a multirate repetitive learning controller. Trans ASME: J Dyn Syst Meas Control 124:668–674CrossRefGoogle Scholar
  4. 4.
    Longman RW (2000) Iterative learning control and repetitive control for engineering practice. Int J Control 73(10):930–954CrossRefzbMATHMathSciNetGoogle Scholar
  5. 5.
    Zhang B, Wang D, Wang Y, Ye Y, Zhou K (2008) Comparison studies on anti-aliasing/anti-imaging filtering and signal extension in multi-rate ILC. In: IFAC World Congress, Seoul, Korea, pp 12468–12473Google Scholar
  6. 6.
    Plotnik AM, Longman RW (1999) Subtleties in the use of zero-phase low-pass filtering and cliff filtering in learning control. Adv Astronaut Sci 103:673–692Google Scholar
  7. 7.
    Zhang B, Wang D, Ye Y, Wang Y, Zhou K (2007) Two-mode ILC with pseudo-downsampled learning in high frequency range. Int J Control 80(3):349–362CrossRefzbMATHMathSciNetGoogle Scholar
  8. 8.
    Longman RW, Wirkander S-L (1998) Automated tuning concepts for iterative learning and repetitive control laws. In: Proceedings of the 37th CDC, FL, USA, pp 192–198Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  1. 1.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore
  2. 2.College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina
  3. 3.Department of Electrical EngineeringUniversity of South CarolinaColumbiaUSA

Personalised recommendations