Title :
Adaptive synchronization of delayed T-S type fuzzy neural networks
Author :
Shunyuan Xiao ; Yijun Zhang ; Baoyong Zhang
Author_Institution :
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
In this letter, the synchronization problem of a class of fuzzy neural networks with time delays is considered. Different from the previous literatures, in the considered master-slave frame, the master system is in form of a general delayed neural networks, and the slave system is described by a T-S fuzzy model which has different parameters with the master system. The considered parameters of the controller are adopted in the adaptive form. By using Lyapunov method, the stability criterion for the error system with adaptive forms of parameters are presented. The synchronization of master system and slave system could be achieved if the obtained conditions are satisfied. Two numerical examples are given to demonstrate the proposed criteria.
Keywords :
Lyapunov methods; delay systems; fuzzy neural nets; stability criteria; synchronisation; Lyapunov method; adaptive synchronization problem; delayed T-S type fuzzy neural networks; error system; master-slave frame system; stability criterion; time delays; Adaptive systems; Delay effects; Delays; Neural networks; Numerical stability; Stability analysis; Synchronization; Neural networks; adaptive synchronization; fuzzy model; parameter unmatched; time delay;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162198