Title :
Chaos synchronization between two different chaotic systems using adaptive interval type-2 FNN control
Author :
Lin, Tsung-Chih ; Hsu, Kang-Wei
Author_Institution :
Dept. of Electron. Eng., Feng-Chia Univ. Taichung, Taichung, Taiwan
Abstract :
A new adaptive interval type-2 fuzzy neural network (FNN) control for chaos synchronization between two different chaotic systems is proposed to handle the training data corrupted by noise or rule uncertainties involving external disturbances. Adaptive interval type-2 FNN control scheme and H∞ tracking approach are incorporated to synchronize two different chaotic systems and the effect of the synchronization error via adaptive fuzzy system relies only on the solution of an algebraic Riccati-like matrix equation. The Laypunov stability theorem has been used to testify the asymptotic stability of the chaotic systems. The simulation example is included to confirm validity and performance of the advocated design methodology.
Keywords :
H∞ control; Lyapunov methods; Riccati equations; adaptive control; asymptotic stability; chaos; fuzzy neural nets; fuzzy systems; linear algebra; matrix algebra; neurocontrollers; nonlinear control systems; H∞ tracking approach; Laypunov stability theorem; adaptive fuzzy system; adaptive interval type-2 FNN control; algebraic Riccati like matrix equation; asymptotic stability; chaos synchronization; fuzzy neural network control; Adaptive control; Adaptive systems; Asymptotic stability; Chaos; Control systems; Fuzzy control; Fuzzy neural networks; Programmable control; Riccati equations; Training data; Adaptive control; chaos synchronization; chaotic system; interval type-2 fuzzy FNN;
Conference_Titel :
Computer Communication Control and Automation (3CA), 2010 International Symposium on
Conference_Location :
Tainan
Print_ISBN :
978-1-4244-5565-2
DOI :
10.1109/3CA.2010.5533754
