Impulsive synchronization for Takagi–Sugeno fuzzy model and its application to continuous chaotic system

2005 ◽  
Vol 339 (3-5) ◽  
pp. 325-332 ◽  
Author(s):  
Yan-Wu Wang ◽  
Zhi-Hong Guan ◽  
Hua O. Wang
Keyword(s):  
Chaotic System ◽  
Fuzzy Model ◽  
Impulsive Synchronization ◽  
Takagi Sugeno

FUZZY PREDICTIVE CONTROLLER FOR UNKNOWN DISCRETE CHAOTIC SYSTEMS

2007 ◽  
Vol 17 (06) ◽  
pp. 2141-2148 ◽  
Author(s):  
ABDELKRIM BOUKABOU ◽  
NOURA MANSOURI
Keyword(s):  
Chaotic System ◽  
Learning Algorithm ◽  
General Structure ◽  
Fuzzy Model ◽  
Model Parameters ◽  
Gaussian Basis Function ◽  
Marquardt Algorithm ◽  
Predictive Controller ◽  
Takagi Sugeno ◽  
Measured Input

In this paper, a fuzzy logic-based approach is taken for modeling and prediction-based control of unknown chaotic system using measured input–output data obtained from the underlying system. Under this framework, a Takagi–Sugeno (TS) fuzzy system is used with a general structure of a linear combination of Gaussian basis function in conjunction with the Levenberg–Marquardt algorithm for the optimization of model parameters. A real-time one-pass learning algorithm is developed for identifying the unknown chaotic system. Based on the fuzzy model above, a predictive controller is achieved for the stabilization of the fuzzy model on unknown unstable fixed points. Several simulation examples are included to illustrate the effectiveness and the feasibility of the proposed method for both fuzzy modeling and predictive control phases.

scholarly journals Aperiodic Sampled-Data Control for Chaotic System Based on Takagi–Sugeno Fuzzy Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Minjie Zheng ◽  
Shenhua Yang ◽  
Lina Li
Keyword(s):  
Chaotic System ◽  
Fuzzy Model ◽  
Sampling Period ◽  
Linear Matrix ◽  
Sampled Data ◽  
Data Control ◽  
Sampled Data Control ◽  
Mean Square Exponential Stability ◽  
Data Controller ◽  
Takagi Sugeno

This paper investigates the aperiodic sampled-data control for a chaotic system. Firstly, Takagi–Sugeno (T-S) fuzzy models for the chaotic systems are established. The lower and upper bounds of the sampling period are taken into consideration. Then, the criteria for mean square exponential stability analysis and aperiodic sampled-data controller synthesis are provided by means of linear matrix inequalities. And the real sampling patterns can be fully captured by constructing suitable Lyapunov functions. Finally, an illustrative example shows that the proposed method is effective to guarantee that the system’s states are stable with aperiodic sampled data.

scholarly journals Observer-Based Fuzzy Control for Memristive Circuit Systems

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Qian Ye ◽  
Xuyang Lou
Keyword(s):  
Fuzzy Control ◽  
Chaotic System ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Chaotic Circuit ◽  
Control Scheme ◽  
Simulation Results ◽  
Memristive Circuit ◽  
Takagi Sugeno

This paper proposes an observer-based fuzzy control scheme for a class of memristive chaotic circuit systems. First, the Takagi-Sugeno fuzzy model is adopted to reconstruct the nonlinear chaotic circuit system. Next, based on the proposed fuzzy model, an observer-based fuzzy controller is developed to estimate the states and stabilize the origin. Third, the results are extended to explore the L∞-gain observer-based fuzzy control for the chaotic system with disturbances. Finally, simulation results are also addressed to show the effectiveness of the proposed control scheme.

scholarly journals Design of PDC Controllers by Matrix Reversibility for Synchronization ofYinandYangChaotic Takagi-Sugeno Fuzzy Henon Maps

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Chun-Yen Ho ◽  
Hsien-Keng Chen ◽  
Zheng-Ming Ge
Keyword(s):  
Chaos Synchronization ◽  
Matrix Theory ◽  
Chinese Philosophy ◽  
Fuzzy Model ◽  
Invertible Matrix ◽  
Henon Maps ◽  
Hénon Maps ◽  
Feminine Principle ◽  
Simulation Results ◽  
Takagi Sugeno

This paper investigates the synchronization ofYinandYangchaotic T-S fuzzy Henon maps via PDC controllers. Based on the Chinese philosophy,Yinis the decreasing, negative, historical, or feminine principle in nature, whileYangis the increasing, positive, contemporary, or masculine principle in nature.YinandYangare two fundamental opposites in Chinese philosophy. The Henon map is an invertible map; so the Henon maps with increasing and decreasing argument can be called theYangandYinHenon maps, respectively. Chaos synchronization ofYinandYangT-S fuzzy Henon maps is achieved by PDC controllers. The design of PDC controllers is based on the linear invertible matrix theory. The T-S fuzzy model ofYinandYangHenon maps and the design of PDC controllers are novel, and the simulation results show that the approach is effective.

scholarly journals Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 823
Author(s):  
Wen-Jer Chang ◽  
Yu-Wei Lin ◽  
Yann-Horng Lin ◽  
Chin-Lin Pen ◽  
Ming-Hsuan Tsai
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Actuator Saturation ◽  
Design Method ◽  
Fuzzy Model ◽  
The Stability ◽  
Interval Type ◽  
Takagi Sugeno

In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure the system performance under the effect of stochastic behaviors, the controller may become bigger even beyond the capacity of practical applications. Therefore, the actuator saturation problem also must be considered in the controller design. The type-2 Takagi-Sugeno (T-S) fuzzy model can describe the parameter uncertainties more completely than the type-1 T-S fuzzy model for a class of nonlinear systems. A fuzzy controller design method is proposed in this paper based on the Interval Type-2 (IT2) T-S fuzzy model for stochastic nonlinear systems subject to actuator saturation. The stability analysis and some corresponding sufficient conditions for the IT2 T-S fuzzy model are developed using Lyapunov theory. Via transferring the stability and control problem into Linear Matrix Inequality (LMI) problem, the proposed fuzzy control problem can be solved by the convex optimization algorithm. Finally, a nonlinear ship steering system is considered in the simulations to verify the feasibility and efficiency of the proposed fuzzy controller design method.

Fuzzy observer–based disturbance rejection control for nonlinear fractional-order systems with time-varying delay

2021 ◽  
pp. 107754632110069
Author(s):  
Parvin Mahmoudabadi ◽  
Mahsan Tavakoli-Kakhki
Keyword(s):  
Fractional Order ◽  
Disturbance Rejection ◽  
State Feedback ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Delayed Systems ◽  
Fuzzy Observer ◽  
Time Varying Delay ◽  
Takagi Sugeno

In this article, a Takagi–Sugeno fuzzy model is applied to deal with the problem of observer-based control design for nonlinear time-delayed systems with fractional-order [Formula: see text]. By applying the Lyapunov–Krasovskii method, a fuzzy observer–based controller is established to stabilize the time-delayed fractional-order Takagi–Sugeno fuzzy model. Also, the problem of disturbance rejection for the addressed systems is studied via the state-feedback method in the form of a parallel distributed compensation approach. Furthermore, sufficient conditions for the existence of state-feedback gains and observer gains are achieved in the terms of linear matrix inequalities. Finally, two numerical examples are simulated for the validation of the presented methods.

Comment on "Stability issues on Takagi-Sugeno fuzzy model-parametric approach" [with reply]

2000 ◽  
Vol 8 (3) ◽  
pp. 345-346 ◽  
Author(s):  
T.A. Johansen ◽  
O. Slupphaug ◽  
Ji-Chang Lo ◽  
Yu-Min Chen
Keyword(s):  
Fuzzy Model ◽  
Parametric Approach ◽  
Stability Issues ◽  
Takagi Sugeno

scholarly journals Further results on robust fuzzy dynamic systems with LMI D-stability constraints

2014 ◽  
Vol 24 (4) ◽  
pp. 785-794 ◽  
Author(s):  
Wudhichai Assawinchaichote
Keyword(s):  
Dynamic Systems ◽  
Fuzzy Controller ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Local System ◽  
Linear Matrix ◽  
Fuzzy Modelling ◽  
Ts Fuzzy Model ◽  
Input Noise ◽  
Takagi Sugeno

Abstract This paper examines the problem of designing a robust H∞ fuzzy controller with D-stability constraints for a class of nonlinear dynamic systems which is described by a Takagi-Sugeno (TS) fuzzy model. Fuzzy modelling is a multi-model approach in which simple sub-models are combined to determine the global behavior of the system. Based on a linear matrix inequality (LMI) approach, we develop a robust H∞ fuzzy controller that guarantees (i) the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value, and (ii) the closed-loop poles of each local system to be within a specified stability region. Sufficient conditions for the controller are given in terms of LMIs. Finally, to show the effectiveness of the designed approach, an example is provided to illustrate the use of the proposed methodology.

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