Automatic Predictive Control Algorithm and Emulation Technique Study
Authors
Zhongguo Yang, Tianfang Cai
Corresponding Author
Zhongguo Yang
Available Online April 2015.
- DOI
- 10.2991/amcce-15.2015.196How to use a DOI?
- Keywords
- Nonlinearity; predictive control; fuzzy neural predictive control; composite particle swarm optimization algorithm
- Abstract
This paper, aiming at the predictive control problem in nonlinear complex system, puts forward fuzzy neural predictive control algorithm based on composite particle swarm optimization algorithm. Under the situation of unknown system model, prediction model is established by combining fuzzy logic with neural network. Meanwhile the effective and feasible predictive control method with well control performance is proposed by making use of composite particle swarm optimization algorithm to complete rolling optimization, so as to provide reliable theoretical foundation for solving practical problems of control system.
- Copyright
- © 2015, 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 - Zhongguo Yang AU - Tianfang Cai PY - 2015/04 DA - 2015/04 TI - Automatic Predictive Control Algorithm and Emulation Technique Study BT - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering PB - Atlantis Press SP - 690 EP - 695 SN - 1951-6851 UR - https://doi.org/10.2991/amcce-15.2015.196 DO - 10.2991/amcce-15.2015.196 ID - Yang2015/04 ER -