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

Hwang, Eun Ju; Hyun, Chang Ho; Kim, Euntai; Park, Mignon

doi:10.1016/j.physleta.2009.03.057

Cited by 56 publications

(29 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1-45 that synchronization is robust and more rapid than it was in It is found that synchronization is robust and quicker but someone need to change the sliding surfaces (s i ) as well as switching gains (k i ) because the same cannot be synchronized at the same sliding surface with same switching gains (Figs. 16,17,18,19,20,21,22,23,24,25,26,27,28,29,30).…”

Section: Numerical Simulationmentioning

confidence: 99%

See 1 more Smart Citation

The improved results with Mathematica and effects of external uncertainty and disturbances on synchronization using a robust adaptive sliding mode controller: a comparative study

Shahzad

2014

Nonlinear Dyn

View full text Add to dashboard Cite

In this computational article, the improved results when different chaotic systems are synchronized using robust adaptive sliding mode controller (RASMC) has been presented in which the simulation is based on Mathematica as well as the effects of external uncertainties (EU) and external disturbances (ED) have been studied in the synchronization of two different chaotic systems. For the same pairs (master and slave systems) of considered chaotic systems (Lorenz, Chen and Liu) and implemented technique (RASMC), a comparative study has been done between the results obtained using Mathematica and MATLAB, as well as the effects of EU and ED on the convergence of synchronization have been studied.

show abstract

Section: Numerical Simulationmentioning

confidence: 99%

“…Similar and worth studies are not limited upto here. It further can be found in [23][24][25][26][27][28][29][30][31][32][33][34][35][36] and the references therein.…”

mentioning

confidence: 96%

The improved results with Mathematica and effects of external uncertainty and disturbances on synchronization using a robust adaptive sliding mode controller: a comparative study

Shahzad

2014

Nonlinear Dyn

View full text Add to dashboard Cite

show abstract

“…Based on the universal approximation capability of the fuzzy systems [25], numerous adaptive fuzzy control schemes [26][27][28][29][30][31][32][33][34][35][36] have been developed for a class of uncertain chaotic systems but with integer order. In these schemes, the adaptive fuzzy systems are used to estimate the model uncertainties.…”

Section: Introductionmentioning

confidence: 99%

“…The robustness issues with respect to the inevitable fuzzy approximation error and the possible external disturbances have been improved by properly adding a robust control term to a dominant adaptive fuzzy controller. Such a robust control term can be conceived using a sliding mode control [27][28][29]33], an H?-based robust control [26,30,31] and a quasi-sliding mode control [32]. However, it is should be mentioned that the above results [26][27][28][29][30][31][32][33][34][35][36] are only applicable to chaotic systems with integer order.…”

Section: Introductionmentioning

confidence: 99%

Projective synchronization of two different fractional-order chaotic systems via adaptive fuzzy control

Bouzeriba

Boulkroune

Bouden

2015

Neural Comput & Applic

View full text Add to dashboard Cite

In this paper, the projective synchronization problem of two fractional-order different chaotic (or hyperchaotic) systems with both uncertain dynamics and external disturbances is considered. More particularly, a fuzzy adaptive control system is investigated for achieving an appropriate projective synchronization of unknown fractional-order chaotic systems. The adaptive fuzzy logic systems are used to approximate some uncertain nonlinear functions appearing in the system model. These latter are augmented by a robust control term to compensate for the unavoidable fuzzy approximation errors and external disturbances as well as residual error due to the use of the socalled e-modification in the adaptive laws. A Lyapunov approach is adopted for the design of the parameter adaptation laws and the proof of the corresponding stability as well as the asymptotic convergence of the underlying synchronization errors towards zero. The effectiveness of the proposed synchronization system is illustrated through numerical experiment results.

show abstract

“…A Lyapunov approach is adopted to carry out the parameter adaptation design, the convergence and the stability analysis involved in the proposed synchronization system. Compared to works in [19,24,29,[36][37][38][46][47][48], the main contributions of this chapter lie in the following:…”

mentioning

confidence: 99%

Projective Synchronization Scheme Based on Fuzzy Controller for Uncertain Multivariable Chaotic Systems

Boulkroune

Bouzeriba

Hamel

2014

Chaos Modeling and Control Systems Design

View full text Add to dashboard Cite

In this chapter, a projective synchronization problem of master-slave chaotic systems is investigated. More specifically, a fuzzy adaptive controller is designed to achieve a projective synchronization of uncertain multivariable chaotic systems. The adaptive fuzzy systems are used to approximate the unknown nonlinear functions. A decomposition property of the control gain matrix is used in the controller design and the stability analysis. A Lyapunov approach is employed to derive the parameter adaptation laws and prove the boundedness of all signals of the closed-loop system as well as the exponential convergence of the synchronization errors to an adjustable region. Numerical simulations are performed to verify the effectiveness of the proposed synchronization system.

show abstract

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

Cited by 56 publications

References 11 publications

The improved results with Mathematica and effects of external uncertainty and disturbances on synchronization using a robust adaptive sliding mode controller: a comparative study

The improved results with Mathematica and effects of external uncertainty and disturbances on synchronization using a robust adaptive sliding mode controller: a comparative study

Projective synchronization of two different fractional-order chaotic systems via adaptive fuzzy control

Projective Synchronization Scheme Based on Fuzzy Controller for Uncertain Multivariable Chaotic Systems

Contact Info

Product

Resources

About