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First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06)
Study of Fuzzy Generalized Predictive Control Algorithm On Nonlinear Systems
Beijing, China
August 30-September 01
ISBN: 0-7695-2616-0
ASCII Text
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Qiang Li, Baocun Qu, Zhiqiang Ge, Xisheng Zhan, "Study of Fuzzy Generalized Predictive Control Algorithm On Nonlinear Systems," Innovative Computing ,Information and Control, International Conference on, vol. 1, pp. 437-440, First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06), 2006.
 
 
BibTex
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@article{ 10.1109/ICICIC.2006.159,
author = {Qiang Li and Baocun Qu and Zhiqiang Ge and Xisheng Zhan},
title = {Study of Fuzzy Generalized Predictive Control Algorithm On Nonlinear Systems},
journal ={Innovative Computing ,Information and Control, International Conference on},
volume = {1},
year = {2006},
isbn = {0-7695-2616-0},
pages = {437-440},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICICIC.2006.159},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Innovative Computing ,Information and Control, International Conference on
TI - Study of Fuzzy Generalized Predictive Control Algorithm On Nonlinear Systems
SN - 0-7695-2616-0
SP437
EP440
A1 - Qiang Li,
A1 - Baocun Qu,
A1 - Zhiqiang Ge,
A1 - Xisheng Zhan,
PY - 2006
KW - null
VL - 1
JA - Innovative Computing ,Information and Control, International Conference on
ER -
 
Qiang Li, Liaoning University of Petroleum & Chemical Technology, China
Baocun Qu, Liaoning University of Petroleum & Chemical Technology, China
Zhiqiang Ge, Liaoning University of Petroleum & Chemical Technology, China
Xisheng Zhan, Liaoning University of Petroleum & Chemical Technology, China
A novel control algorithm-fuzzy generalized predictive control (FGPC) algorithm for nonlinear systems is proposed. Fuzzy Gustafon-Kessel algorithm and weighted recursive least-square method are applied to identify the T-S model off-line. The identified model is then combined with generalized predictive control algorithm to control non-linear systems. And the detailed steps of the algorithm have been given. The simulation results prove that the proposed algorithm has a high degree of identification accuracy, good robustness, and has obtained a good control result, and therefore is applicable for a variety of non-linear systems.
Citation:
Qiang Li, Baocun Qu, Zhiqiang Ge, Xisheng Zhan, "Study of Fuzzy Generalized Predictive Control Algorithm On Nonlinear Systems," icicic, vol. 1, pp.437-440, First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06), 2006
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