Adelaide Research & Scholarship
Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/78261
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| Type: | Journal article |
| Title: | A novel identification method for generalized T-S fuzzy systems |
| Author: | Huang, L. Wang, K. Shi, P. Karimi, H. |
| Citation: | Mathematical Problems in Engineering, 2012; 2012:1-12 |
| Publisher: | Gordon Breach Sci Publ Ltd |
| Issue Date: | 2012 |
| ISSN: | 1024-123X 1563-5147 |
| Statement of Responsibility: | Ling Huang, Kai Wang, Peng Shi and Hamid Reza Karimi |
| Abstract: | In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm. |
| Description: | Extent: 12p. |
| Rights: | Copyright © 2012 Ling Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| DOI: | 10.1155/2012/893807 |
| Appears in Collections: | Aurora harvest 4 Electrical and Electronic Engineering publications |
Files in This Item:
| File | Description | Size | Format | |
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| hdl_78261.pdf | Published version | 1.56 MB | Adobe PDF | View/Open |
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