Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network

Lan Wang; Yu Cheng; Jinglu Hu

doi:10.1109/IJCNN.2010.5596819

Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network

Lan Wang^*, Yu Cheng, Jinglu Hu

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

This paper presents a novel approach for designing adaptive controller of nonlinear dynamical systems based on an improved quasi-ARX neural network prediction model. The improved quasi-ARX neural network prediction model has two parts: the linear part is used for stability and the nonlinear part is used to satisfy accuracy requirement. Then, we can obtain a linear controller and a nonlinear controller based on the characteristic of the improved quasi-ARX neural network prediction model. A fuzzy switching algorithm is designed between the two controllers. Theory analysis and simulations are given to show the effectiveness of the proposed method both on stability and accuracy.

Original language	English
Title of host publication	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
DOIs	https://doi.org/10.1109/IJCNN.2010.5596819
Publication status	Published - 2010
Event	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona, Spain Duration: 2010 Jul 18 → 2010 Jul 23

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks

Conference

Conference	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
Country/Territory	Spain
City	Barcelona
Period	10/7/18 → 10/7/23

ASJC Scopus subject areas

Software
Artificial Intelligence

Access to Document

10.1109/IJCNN.2010.5596819

Cite this

Wang, L., Cheng, Y., & Hu, J. (2010). Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 Article 5596819 (Proceedings of the International Joint Conference on Neural Networks). https://doi.org/10.1109/IJCNN.2010.5596819

Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network. / Wang, Lan; Cheng, Yu; Hu, Jinglu.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010. 2010. 5596819 (Proceedings of the International Joint Conference on Neural Networks).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wang, L, Cheng, Y & Hu, J 2010, Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010., 5596819, Proceedings of the International Joint Conference on Neural Networks, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, 10/7/18. https://doi.org/10.1109/IJCNN.2010.5596819

Wang L, Cheng Y, Hu J. Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010. 2010. 5596819. (Proceedings of the International Joint Conference on Neural Networks). doi: 10.1109/IJCNN.2010.5596819

@inproceedings{96ff6f62c4184eb2858115daaef36128,

title = "Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network",

abstract = "This paper presents a novel approach for designing adaptive controller of nonlinear dynamical systems based on an improved quasi-ARX neural network prediction model. The improved quasi-ARX neural network prediction model has two parts: the linear part is used for stability and the nonlinear part is used to satisfy accuracy requirement. Then, we can obtain a linear controller and a nonlinear controller based on the characteristic of the improved quasi-ARX neural network prediction model. A fuzzy switching algorithm is designed between the two controllers. Theory analysis and simulations are given to show the effectiveness of the proposed method both on stability and accuracy.",

author = "Lan Wang and Yu Cheng and Jinglu Hu",

year = "2010",

doi = "10.1109/IJCNN.2010.5596819",

language = "English",

isbn = "9781424469178",

series = "Proceedings of the International Joint Conference on Neural Networks",

booktitle = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010",

note = "2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 ; Conference date: 18-07-2010 Through 23-07-2010",

}

TY - GEN

T1 - Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network

AU - Wang, Lan

AU - Cheng, Yu

AU - Hu, Jinglu

PY - 2010

Y1 - 2010

N2 - This paper presents a novel approach for designing adaptive controller of nonlinear dynamical systems based on an improved quasi-ARX neural network prediction model. The improved quasi-ARX neural network prediction model has two parts: the linear part is used for stability and the nonlinear part is used to satisfy accuracy requirement. Then, we can obtain a linear controller and a nonlinear controller based on the characteristic of the improved quasi-ARX neural network prediction model. A fuzzy switching algorithm is designed between the two controllers. Theory analysis and simulations are given to show the effectiveness of the proposed method both on stability and accuracy.

AB - This paper presents a novel approach for designing adaptive controller of nonlinear dynamical systems based on an improved quasi-ARX neural network prediction model. The improved quasi-ARX neural network prediction model has two parts: the linear part is used for stability and the nonlinear part is used to satisfy accuracy requirement. Then, we can obtain a linear controller and a nonlinear controller based on the characteristic of the improved quasi-ARX neural network prediction model. A fuzzy switching algorithm is designed between the two controllers. Theory analysis and simulations are given to show the effectiveness of the proposed method both on stability and accuracy.

UR - http://www.scopus.com/inward/record.url?scp=79959407267&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79959407267&partnerID=8YFLogxK

U2 - 10.1109/IJCNN.2010.5596819

DO - 10.1109/IJCNN.2010.5596819

M3 - Conference contribution

AN - SCOPUS:79959407267

SN - 9781424469178

T3 - Proceedings of the International Joint Conference on Neural Networks

BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

Y2 - 18 July 2010 through 23 July 2010

ER -

Nonlinear adaptive control using a fuzzy switching mechanism based on improved quasi-ARX neural network

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this