Title :
Stability Analysis of Takagi–Sugeno Fuzzy Cellular Neural Networks With Time-Varying Delays
Author :
Hou, Yi-You ; Liao, Teh-Lu ; Yan, Jun-Juh
Author_Institution :
Dept. of Eng. Sci, Nat. Cheng Kung Univ., Tainan
fDate :
6/1/2007 12:00:00 AM
Abstract :
This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov-Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov-Krasovskii functional, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results
Keywords :
Lyapunov matrix equations; asymptotic stability; cellular neural nets; delay systems; delays; fuzzy control; fuzzy neural nets; linear matrix inequalities; neurocontrollers; time-varying systems; Lyapunov-Krasovskii functional theory; Takagi-Sugeno fuzzy cellular neural networks; conservative delay-dependent stability criterion; global exponential stability problem; linear matrix inequality technique; time-varying delays; Cellular neural networks; Delay effects; Fuzzy neural networks; Fuzzy systems; Linear matrix inequalities; Neural networks; Nonlinear systems; Stability analysis; Stability criteria; Sufficient conditions; Cellular neural networks (CNNs); Lyapunov–Krasovskii functional theory; Takagi–Sugeno (T–S) fuzzy model; linear matrix inequality (LMI); time-varying delay; Algorithms; Computer Simulation; Markov Chains; Models, Statistical; Neural Networks (Computer); Nonlinear Dynamics; Pattern Recognition, Automated; Stochastic Processes;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2006.889628
