Model identification of a servo-tracking system using fuzzy clustering

Authors
Nguyen, EM Prasad, NR
Citation
Em. Nguyen et Nr. Prasad, Model identification of a servo-tracking system using fuzzy clustering, INT J UNC F, 7(4), 1999, pp. 337-346
Citations number
26
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
ISSN journal
02184885 → ACNP
Volume
7
Issue
4
Year of publication
1999
Pages
337 - 346
Database
ISI
SICI code
0218-4885(199908)7:4<337:MIOASS>2.0.ZU;2-8
Abstract
This paper investigates the use of Fuzzy Clustering as a means for model id entification of a complex and highly non-linear servo-tracking system when only observational data is available. The use of Fuzzy Clustering facilitat es automatic generation of rules and its antecedent parameters. The consequ ent of the model is then formulated in the form of Takagi, Sugeno and Kang (TSK), and its parameters determined by the Least Squares Method (LSM).