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A Direct Adaptive Predictive Functional Control Based on T-S Fuzzy Model
Jinan, China October 16-October 18
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISDA.2006.1Sixth International Conference on Int ...
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Chengli Su, Ping Li, Shuqing Wang, "A Direct Adaptive Predictive Functional Control Based on T-S Fuzzy Model," Intelligent Systems Design and Applications, International Conference on, vol. 3, pp. 92-97, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 3, 2006.
 
 
BibTex
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@article{ 10.1109/ISDA.2006.1,
author = {Chengli Su and Ping Li and Shuqing Wang},
title = {A Direct Adaptive Predictive Functional Control Based on T-S Fuzzy Model},
journal ={Intelligent Systems Design and Applications, International Conference on},
volume = {3},
year = {2006},
isbn = {0-7695-2528-8},
pages = {92-97},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISDA.2006.1},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Intelligent Systems Design and Applications, International Conference on
TI - A Direct Adaptive Predictive Functional Control Based on T-S Fuzzy Model
SN - 0-7695-2528-8
SP92
EP97
A1 - Chengli Su,
A1 - Ping Li,
A1 - Shuqing Wang,
PY - 2006
KW - Nonlinear systems
KW - T-S fuzzy model
KW - Predictive functional control
KW - Adaptive control
VL - 3
JA - Intelligent Systems Design and Applications, International Conference on
ER -
 
Chengli Su, Liaoning University of Petroleum & Chemical Technology, China
Ping Li, Liaoning University of Petroleum & Chemical Technology, China
Shuqing Wang, Zhejiang University, China
An adaptive predictive functional control algorithm based on T-S fuzzy model for discrete-time nonlinear systems is proposed. In this algorithm the consequent parameters of T-S fuzzy model are identified by the weighting recursive least square method, Parameters of the fuzzy model are used to directly recursively compute the model prediction output, and needn?t solve Diophantine equations. Analysis solution of the. predictive control input is derived. Simulation result shows that the proposed algorithm is an effective control strategy with excellent tracing ability and strong robustness.
Index Terms:
Nonlinear systems, T-S fuzzy model, Predictive functional control, Adaptive control
Citation:
Chengli Su, Ping Li, Shuqing Wang, "A Direct Adaptive Predictive Functional Control Based on T-S Fuzzy Model," isda, vol. 3, pp.92-97, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 3, 2006
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