SYNCHRONIZATION OF UNCERTAIN CHAOTIC SYSTEMS BASED ON THE FUZZY-MODEL-BASED APPROACH

2006 ◽  
Vol 16 (05) ◽  
pp. 1435-1444 ◽  
Author(s):  
H. K. LAM ◽  
F. H. F. LEUNG
Keyword(s):  
Chaotic Systems ◽  
Fuzzy Model ◽  
Parameter Design ◽  
Parameter Uncertainties ◽  
Model Based ◽  
Synchronization Problem ◽  
Programming Techniques ◽  
Uncertain Chaotic Systems ◽  
Switching Controller ◽  
The Stability

This paper investigates the synchronization of chaotic systems subject to parameter uncertainties. Based on the fuzzy-model-based approach, a switching controller will be proposed to deal with the synchronization problem. The stability conditions will be derived based on the Lyapunov approach. The tracking performance and parameter design of the proposed switching controller will be formulated as a generalized eigenvalue minimization problem which can be solved numerically using some convex programming techniques. Simulation examples will be given to show the effectiveness of the proposed approach.

FUZZY MODEL-BASED APPROACH TO CHAOTIC ENCRYPTION USING SYNCHRONIZATION

2003 ◽  
Vol 13 (01) ◽  
pp. 215-225 ◽  
Author(s):  
KUANG-YOW LIAN ◽  
PETER LIU ◽  
CHIAN-SONG CHIU ◽  
TUNG-SHENG CHIANG
Keyword(s):  
Discrete Time ◽  
Chaotic Systems ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Chaotic Encryption ◽  
Communication Structure ◽  
Model Based ◽  
Synchronization Problem ◽  
Chaotic Signals ◽  
Selection Of

This paper proposes a fuzzy model-based chaotic encryption approach using synchronization. The cryptosystem uses T–S fuzzy models to exactly represent discrete-time chaotic systems into separate linear systems. Then the synchronization problem is solved using linear matrix inequalities. The advantages of this approach are: the general and systematic T–S fuzzy model design methodology suitable for well-known Luré type discrete-time chaotic systems; flexibility in selection of chaotic signals for cryptosystem secure key generator; and multiuser capabilities. Especially taking a chaotic superincreasing sequence as an encryption key enhances the chaotic communication structure to a higher-level of security compared to traditional masking methods. In addition, numerical simulations and DSP-based experiments are carried out to verify the validity of theoretical results.

Fuzzy-Model-Based Adaptive Control for a Kind of Discrete-Time Systems with Time-Delay and Disturbances

2014 ◽  
Vol 22 (03) ◽  
pp. 453-468
Author(s):  
Yi-Min Li ◽  
Yuan-Yuan Li
Keyword(s):  
Adaptive Control ◽  
Stability Analysis ◽  
Time Delay ◽  
Discrete Time ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Parameter Uncertainties ◽  
Model Based ◽  
The Stability

This paper presents the stability analysis of discrete-time fuzzy-model-based adaptive control systems with time-delay, parameter uncertainties and external disturbance. To facilitate the stability analysis, the T-S fuzzy model is employed to represent the discretetime nonlinear system. A fuzzy observer is used to estimate the state of the fuzzy system, by using the estimations of states and nonlinear functions, and sufficient conditions for designing observer-based fuzzy controllers are proposed. The control and observer matrices involved can be determined by solving a set of linear matrix inequality (LMI). Finally, the numerical example carried out also demonstrate the feasibility of the design method.

Fuzzy Control for Nonlinear Uncertain T-S Fuzzy Systems with Time-Varying Delays

2013 ◽  
Vol 341-342 ◽  
pp. 668-673
Author(s):  
Yi Min Li ◽  
Yuan Yuan Li
Keyword(s):  
Stability Analysis ◽  
Discrete Time ◽  
Fuzzy Model ◽  
Optimization Techniques ◽  
Linear Matrix ◽  
Time Varying ◽  
Parameter Uncertainties ◽  
Lmi Optimization ◽  
System A ◽  
The Stability

This paper studies the stability analysis of discrete time-varying system with parameter uncertainties and disturbances. The system under consideration is subject to time-varying non-bounded parameter uncertainties in both the state and measured output matrices. To facilitate the stability analysis, the T-S fuzzy model is employed to represent the discrete-time nonlinear system. A fuzzy observer is used to guarantee the Lyapunov stability of the closed-loop system and reduces the effect of the disturbance input on the controlled output to a prescribed level for all admissible uncertainties. The control and observer matrices can be obtained by directly solving a set of linear matrix inequality (LMI) via the existing LMI optimization techniques. Finally, an example is provided to demonstrate the effectiveness of the proposed approach.

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