Iterative Learning Control Based on Niche Shuffled Frog Leaping Algorithm Research
- 10.2991/amcce-17.2017.29How to use a DOI?
- Nonlinear system; Norm optimization; Parameter optimization; Niche shuffled frog leaping Algorithm.
Aiming at slow convergence and low precision optimization in iterative learning control, a niche shuffled frog leaping algorithm was proposed in this paper, which combined memes algorithm and particle swarm algorithm, using the niche shuffled frog leaping algorithm based on the restrictive competition, avoiding the paedogenesis effectively improving the convergence speed and optimization accuracy. In order to achieve less error and monotone convergence in the iterative domain, get better transient tracking performance and establish a fast PID parameter optimization iterative learning control algorithm based on the discrete norm performance index, the PID controller was introduced into the iterative learning control parameter optimization algorithm to expand the algorithm's dimension, increase the degree of freedom in the optimal parameters, and ultimately promote the learning efficiency.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiaohong Hao AU - Dongjiang Wang PY - 2017/03 DA - 2017/03 TI - Iterative Learning Control Based on Niche Shuffled Frog Leaping Algorithm Research BT - Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2017) PB - Atlantis Press SP - 166 EP - 172 SN - 2352-5401 UR - https://doi.org/10.2991/amcce-17.2017.29 DO - 10.2991/amcce-17.2017.29 ID - Hao2017/03 ER -