Automatic Predictive Control Algorithm and Emulation Technique Study

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/).

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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  -