Non-uniform Trajectory Tracking AILC for Nonlinear Time-varying Parameter System with Multiple Unknown Control Directions

Authors

  • Chunli Zhang Xi’an University of Technology, Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing
  • Yangjie Gao Xi’an University of Technology, Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing
  • Lei Yan Xi’an University of Technology, Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing
https://doi.org/10.61383/ejam.20231127

Keywords:

Iterative learning control, Time-varying parameter systems, Lyapunov-like, Multiple unknown control directions, Non-uniform target tracking

Abstract

In this paper, a new iterative learning controller is presented for nonlinear time-varying parameter system to solve the tracking problem of different target trajectories. Based on Nussbaum function and the Lyapunov-like synthesis design the learning controller to handle system dynamics with multi-unknown control directions. Over a finite time interval, the unknown time-varying parameter is considered to be periodic, so it is expanded using a Fourier series expansion, and the remaining terms are treated with a canonical series. The controller designed in this paper can ensure that all signals of the closed-loop system are bounded in a finite time interval [0,T], and can complete non-uniform target tracking. Finally, a simulation example is given to verify the effectiveness of the designed controller.

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Published

2023 May 09

How to Cite

[1]
C. Zhang, Y. Gao, and L. Yan, “Non-uniform Trajectory Tracking AILC for Nonlinear Time-varying Parameter System with Multiple Unknown Control Directions”, Electron. J. Appl. Math., vol. 1, no. 1, pp. 81–100, May 2023.

Issue

Vol. 1 No. 1 (2023)

Section

Research Article

License

Copyright (c) 2023 Chunli Zhang (Corresponding Author); Yangjie Gao, Lei Yan

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
 
 
Received 2023 Mar 20
Accepted 2023 May 03
Published 2023 May 09

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