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Wavelet transform-based frequency tuning ILC.

Bin Zhang1, Danwei Wang, Yongqiang Ye

  • 1School of Electrical and Electronics Engineering, Nanyang Technological University, Nanyang, Singapore 639798. binzhang@pmail.ntu.edu.sg

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|February 22, 2005
PubMed
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This study introduces a discrete wavelet transform method to dynamically adjust filter cutoff frequencies, improving tracking accuracy by adapting to error components in real-time. This enhances both transient and long-term system stability.

Area of Science:

  • Control Systems Engineering
  • Signal Processing

Background:

  • Accurate tracking is crucial in dynamic systems.
  • Traditional filters struggle with time-varying error components and noise.

Purpose of the Study:

  • To propose a novel discrete wavelet transform-based method for adaptive cutoff frequency tuning.
  • To experimentally validate the effectiveness of the proposed method in improving tracking stability.

Main Methods:

  • Utilizing the discrete wavelet packet algorithm for time-frequency analysis of tracking errors.
  • Decomposing errors into frequency regions to identify maximal error components.
  • Dynamically adjusting the filter's passband based on the identified maximal error frequency.

Main Results:

Related Experiment Videos

  • The method successfully suppresses higher frequency error components at appropriate time steps.
  • Lower cutoff frequencies are employed during low-frequency error dominance, reducing noise influence.
  • Adaptive filtering demonstrated improved transient and long-term stability.

Conclusions:

  • The proposed discrete wavelet transform method offers an effective approach for adaptive filter tuning in tracking systems.
  • Real-time adjustment of cutoff frequency based on error component analysis enhances system performance and stability.