Adaptive synchronization of complicated chaotic systems with uncertainties via fuzzy modeling-based control strategy

UM > Faculty of Science and Technology > DEPARTMENT OF ELECTROMECHANICAL ENGINEERING

Status	已發表Published
	Adaptive synchronization of complicated chaotic systems with uncertainties via fuzzy modeling-based control strategy
	Tam, L. M.; Chen, H. K.; Li, S. Y.
	2018-02-01
Source Publication	Information Science
ISSN	0020-0255
Pages	18-31
Abstract	In this paper, adaptive control of complicated chaotic systems with unknown parameters is discussed via a set of fuzzy modeling-based adaptive strategy. The proposed fuzzy model theory aims to adjust the inner-weighting of each linear sub-equation, simplize the complicated modeling process, and to reveal the similar behaviors of complicated nonlinear dynamic system. Further, based on the modeling concept, a set of fuzzy model-based adaptive control scheme and its creative fuzzy update laws of parameters are proposed to achieve the goal of adaptive synchronization. Two identical complicated dynamic systems, Mathieu-Van der Pol system (M-V system) with uncertainties, are designed and ilustrated for numerical simulation example to show the effectiveness and feasibility of the proposed novel adaptive control strategy.
Keyword	GLT fuzzy model nonlinear terms group fuzzy adaptive control
Language	英語English
The Source to Article	PB_Publication
PUB ID	40932
Document Type	Journal article
Collection	DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Corresponding Author	Li, S. Y.
Recommended Citation GB/T 7714	Tam, L. M.,Chen, H. K.,Li, S. Y.. Adaptive synchronization of complicated chaotic systems with uncertainties via fuzzy modeling-based control strategy[J]. Information Science, 2018, 18-31.
APA	Tam, L. M.., Chen, H. K.., & Li, S. Y. (2018). Adaptive synchronization of complicated chaotic systems with uncertainties via fuzzy modeling-based control strategy. Information Science, 18-31.
MLA	Tam, L. M.,et al."Adaptive synchronization of complicated chaotic systems with uncertainties via fuzzy modeling-based control strategy".Information Science (2018):18-31.

Files in This Item:
There are no files associated with this item.

If you have any objections to this item, please fill out the form below and the administrator will contact you as soon as possible.
Content:
Email：	*
Affiliation No.
Verification Code:	Refresh

Any comments and suggestions are welcomed.
Title:	*
Content:
Email：	*
Verification Code:	Refresh