Fuzzy model based adaptive synchronization of uncertain chaotic systems: Robust tracking control approach

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.

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A novel fuzzy disturbance observer-based robust tracking control approach for a class of uncertain nonlinear MIMO systems

2010 2nd International Conference on Advanced Computer Control ◽

10.1109/icacc.2010.5487051 ◽

2010 ◽

Cited By ~ 1

Author(s):

Hu Hui ◽

Hu Jun-da ◽

Peng Guo

Keyword(s):

Tracking Control ◽

Disturbance Observer ◽

Mimo Systems ◽

Robust Tracking ◽

Robust Tracking Control ◽

Control Approach ◽

Fuzzy Disturbance Observer

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Adaptive Synchronization of Fractional Hyper-Chaotic System with Unknown Parameters

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.850-851.868 ◽

2013 ◽

Vol 850-851 ◽

pp. 868-871 ◽

Cited By ~ 1

Author(s):

Li Xin Yang ◽

Wan Sheng He ◽

Jin Ping Jia ◽

Fan Di Zhang

Keyword(s):

Fractional Order ◽

Tracking Control ◽

Chaos Synchronization ◽

Chaotic Systems ◽

Adaptive Synchronization ◽

Uncertain Parameters ◽

Unknown Parameters ◽

Fractional Systems ◽

Control Approach ◽

The Stability

In this paper, chaos synchronization of the modified Sprott E system is investigated. Based on the stability theorem for fractional systems, tracking control approach is used for the fractional-order systems with uncertain parameters. Meanwhile, suitable adaptive synchronization controller and recognizing rules of the uncertain parameters are designed. Numerical simulation results show that the method is easy to implement and reliable for synchronizing the two nonlinear fractional order hyper-chaotic systems.

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Adaptive Synchronization of Uncertain Chaotic Systems Based on T–S Fuzzy Model

IEEE Transactions on Fuzzy Systems ◽

10.1109/tfuzz.2006.880007 ◽

2007 ◽

Vol 15 (3) ◽

pp. 359-369 ◽

Cited By ~ 52

Author(s):

Jae-Hun Kim ◽

Chang-Ho Hyun ◽

Euntai Kim ◽

Mignon Park

Keyword(s):

Chaotic Systems ◽

Fuzzy Model ◽

Adaptive Synchronization ◽

Uncertain Chaotic Systems

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Dynamic model based robust tracking control of a differentially steered wheeled mobile robot

Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207) ◽

10.1109/acc.1998.703528 ◽

1998 ◽

Cited By ~ 6

Author(s):

Yulin Zhang ◽

Daehie Hong ◽

J.H. Chung ◽

S.A. Velinsky

Keyword(s):

Mobile Robot ◽

Dynamic Model ◽

Tracking Control ◽

Wheeled Mobile Robot ◽

Robust Tracking ◽

Robust Tracking Control ◽

Model Based

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T-S Fuzzy Control of Uncertain Chaotic Vibration

Shock and Vibration ◽

10.1155/2012/368207 ◽

2012 ◽

Vol 19 (3) ◽

pp. 379-389 ◽

Cited By ~ 1

Author(s):

Abdelkrim Boukabou ◽

Noura Mansouri

Keyword(s):

Fuzzy Logic ◽

Fuzzy Control ◽

Chaos Control ◽

Chaotic Systems ◽

Fuzzy Model ◽

Control Approach ◽

Chaotic Vibration ◽

Uncertain Chaotic Systems ◽

Simulation Results ◽

Takagi Sugeno

We present in this paper a novel and unified control approach that combines intelligent fuzzy logic methodology with predictive method for controlling chaotic vibration of a class of uncertain chaotic systems. We first introduce prediction into each subsystem of Takagi Sugeno (T-S) fuzzy IF-THEN rules and then present a unified T-S predictive fuzzy model for chaos control. The proposed controller can successfully stabilize the chaos and track the desired targets. The simulation results illustrate its effectiveness.

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