Variable Gain for Iterative Learning Control

Title:Variable Gain for Iterative Learning Control

Volume: 14 Issue: 3

Author(s): Jianhuan Su, Yinjun Zhang*Mengji Chen

Affiliation:

• School of Physics and Electrical Engineering, Hechi University, Yizhou-546300, Guangxi,China

Keywords: Iterative learning control, variable gain, parameter optimization, convergence analysis, MATLAB, algorithm.

Abstract:

Background: At present, the gain of most ILC algorithms is fixed, and the convergence speed of the system depends on the learning law, which will lead to the complexity of the structure of the learning law, and variable gain can accelerate the convergence speed without changing the structure of the learning law as variable gains are introduced into ILC.

Objective: In this paper, the D-type learning law is used. Firstly, the variable gain iterative learning controller is designed. Secondly, the convergence of the learning law is analyzed.

Methods: Finally, in order to illustrate the effectiveness of this method, the simulation is carried out using MATLAB.

Results and Conclusion: The simulation results show that the variable gain iterative learning control can improve the convergence speed of the iteration, and weaken the restrictions on the initial input.

Cite this article as:

Su Jianhuan , Zhang Yinjun *, Chen Mengji , Variable Gain for Iterative Learning Control, Recent Advances in Computer Science and Communications 2021; 14 (3) . https://dx.doi.org/10.2174/2666255813666190912100716