A course in fuzzy systems and control
A course in fuzzy systems and control
Nonlinear Control Systems
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Robust H∞ control for discrete-time fuzzy systems via basis-dependent Lyapunov functions
Information Sciences: an International Journal
H∞ filtering of discrete-time fuzzy systems via basis-dependent Lyapunov function approach
Fuzzy Sets and Systems
A New Fuzzy Lyapunov Approach to Non-Quadratic Stabilization of Takagi-Sugeno Fuzzy Models
International Journal of Applied Mathematics and Computer Science
Output tracking and regulation of nonlinear system based onTakagi-Sugeno fuzzy model
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Comments on "Output tracking and regulation of nonlinear system based on Takagi-Sugeno fuzzy model"
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A multiple Lyapunov function approach to stabilization of fuzzy control systems
IEEE Transactions on Fuzzy Systems
The fuzzy discrete-time robust regulation problem: an LMI approach
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Synchronization of Duffing-Holmes oscillators using stable neural network controller
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part III
Hi-index | 0.20 |
In this paper, some results on fuzzy regulation and fuzzy modeling are presented for synchronization of chaotic systems described by Takagi-Sugeno (TS) fuzzy models using linear local controllers. It is shown that the synchronization error is bounded if the local controller can be appropriately designed, and that such an error is independent of initial conditions. This feature allows synchronizing not only similar chaotic systems but, under certain conditions, different chaotic systems can be synchronized as well. In other words, this approach can be used to obtain either complete or generalized synchronization. Several simulations are carried out to illustrate how the problem can be solved in a practical way by using the linear matrix inequalities (LMI) technique.