Synchronous and Asynchronous Iterative Learning Strategies of T-S Fuzzy Systems with Measurable and Unmeasurable State Information

Xiong, W, Xu, L, Ho, D, Cao, J and Huang, T 2018, 'Synchronous and Asynchronous Iterative Learning Strategies of T-S Fuzzy Systems with Measurable and Unmeasurable State Information', IEEE Transactions on Fuzzy Systems, vol. 26, no. 5, pp. 3042-3053.


Document type: Journal Article
Collection: Journal Articles

Title Synchronous and Asynchronous Iterative Learning Strategies of T-S Fuzzy Systems with Measurable and Unmeasurable State Information
Author(s) Xiong, W
Xu, L
Ho, D
Cao, J
Huang, T
Year 2018
Journal name IEEE Transactions on Fuzzy Systems
Volume number 26
Issue number 5
Start page 3042
End page 3053
Total pages 12
Publisher IEEE
Abstract By designing synchronous and asynchronous iterative learning controllers, the tracking problem of Takagi-Sugeno (T-S) fuzzy systems with measurable and unmeasurable state information is investigated in this paper. The T-S fuzzy model is first constructed to describe dynamic systems with a variable structure. Iterative learning controllers are then designed to achieve the tracking problem of T-S fuzzy systems. Here, the iterative learning controllers are designed to be synchronous and asynchronous. Also, system states are considered to be measurable and unmeasurable due to the capability of transmission bandwidth of networks and external and/or internal disturbances. Finally, simulation results are given to illustrate the usefulness of the developed criteria.
Subject Artificial Intelligence and Image Processing not elsewhere classified
Keyword(s) Asynchronous iterative learning controllers
measurable and unmeasurable state information
synchronous iterative learning controllers
Takagi-Sugeno (T-S) fuzzy systems
DOI - identifier 10.1109/TFUZZ.2017.2787156
Copyright notice © 2017 IEEE.
ISSN 1063-6706
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