Chun-Li Zhang and Jun-Min Li. Adaptive Iterative Learning Control of Non-uniform Trajectory Tracking for Strict Feedback Nonlinear Time-varying Systems. International Journal of Automation and Computing, vol. 11, no. 6, pp. 621-626, 2014. https://doi.org/10.1007/s11633-014-0819-0
Citation: Chun-Li Zhang and Jun-Min Li. Adaptive Iterative Learning Control of Non-uniform Trajectory Tracking for Strict Feedback Nonlinear Time-varying Systems. International Journal of Automation and Computing, vol. 11, no. 6, pp. 621-626, 2014. https://doi.org/10.1007/s11633-014-0819-0

Adaptive Iterative Learning Control of Non-uniform Trajectory Tracking for Strict Feedback Nonlinear Time-varying Systems

doi: 10.1007/s11633-014-0819-0
Funds:

This work was supported by National Natural Science Foundation of China (No. 60974139) and Fundamental Research Funds for the Central Universities (No. 72103676).

  • Received Date: 2012-07-30
  • Rev Recd Date: 2014-02-14
  • Publish Date: 2014-12-20
  • In this paper, an iterative learning control strategy is presented for a class of nonlinear time-varying systems, the timevarying parameters are expanded into Fourier series with bounded remainder term. The backstepping design technique is used to deal with system dynamics with non-global Lipschitz nonlinearities and the approach proposed in this paper solves the non-uniform trajectory tracking problem. Based on the Lyapunov-like synthesis, the proposed method shows that all signals in the closed-loop system remain bounded over a pre-specified time interval [0, T]. And perfect non-uniform trajectory tracking of the system output is completed. A typical series is introduced in order to deal with the unknown bound of remainder term. Finally, a simulation example shows the feasibility and effectiveness of the approach.

     

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