F.M. Moukam Kakmeni
University of Yaoundé I
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Publication
Featured researches published by F.M. Moukam Kakmeni.
Physics Letters A | 2003
Samuel Bowong; F.M. Moukam Kakmeni
This Letter presents a robust control scheme for a class of uncertain chaotic systems in the canonical form, with unknown nonlinearities. To cope with the uncertainties, we combine Lyapunov methodology with observer design. The proposed strategy comprises an exponential linearizing feedback and an uncertainty estimator. The developed control scheme allows chaos suppression. The advantage of this method over the existing results is that the control time is explicitly computed. Simulations studies are conducted to verify the effectiveness of the scheme.
Journal of Computational and Nonlinear Dynamics | 2006
M. Siewe Siewe; F.M. Moukam Kakmeni; C. Tchawoua; P. Woafo
The nonlinear response and suppression of chaos by weak harmonic perturbation inside a triple well Φ 6 -Rayleigh oscillator combined to parametric excitations is studied in this paper. The main attention is focused on the dynamical properties of local bifurcations as well as global bifurcations including homoclinic and heteroclinic bifurcations. The original oscillator is transformed to averaged equations using the method of harmonic balance to obtain periodic solutions. The response curves show the saddle-node bifurcation and the multi-stability phenomena. Based on the Melnikovs method, horseshoe chaos is found and its control is made by introducing an external periodic perturbation.
International Journal of Bifurcation and Chaos | 2006
Samuel Bowong; A. Temgoua Kagou; F.M. Moukam Kakmeni
This paper proposes an adaptive observer-based synchronization of continuous-time chaotic systems. Our method concerns any chaotic system that comprises uncertainties. Using the Lyapunov stability theory, we show that the synchronization of two coupled chaotic systems can be achieved by means of a linear coupling. A remarkable feature of the proposed approach is that it is robust with respect to noise and parameter mismatch. Numerical simulation of the Chuas circuit verifies the efficiency and effectiveness of the proposed adaptive synchronization scheme.
International Journal of Bifurcation and Chaos | 2006
Hilaire Fotsin; F.M. Moukam Kakmeni; Samuel Bowong
This Letter studies adaptive chaos synchronization between two coupled nonlinear electrical circuits using a linear state feedback. A simple and yet easily applicable algorithm is derived for adaptive chaos synchronization based on the Lyapunov stability theory. An adaptive linear state feedback is derived such that the coupled systems are globally synchronized. Numerical simulations show the effectiveness of the proposed synchronization scheme. A Pspice simulation of the adaptive synchronization process is performed to confirm the numerical results.
International Journal of Bifurcation and Chaos | 2007
F.M. Moukam Kakmeni; Samuel Bowong
This work studies transitions to chaos and adaptive synchronization of a nonlinear emitter–receiver system in a drive–response framework. Safe bifurcations and explosive bifurcations are observed. A robust adaptive observer-based response system is designed to synchronize the emitter–receiver system with unknown parameters and external disturbances. Lyapunov stability ensures global synchronization between the drive and response systems even if Lipschitz constants on functions matrices and bound on uncertainties are unknown. Computer simulations are provided to illustrate the designed adaptive synchronization scheme.
Chaos Solitons & Fractals | 2004
Samuel Bowong; F.M. Moukam Kakmeni
Physics Letters A | 2004
F.M. Moukam Kakmeni; Samuel Bowong; C. Tchawoua; Ernest Kaptouom
Physica A-statistical Mechanics and Its Applications | 2005
M. Siewe Siewe; F.M. Moukam Kakmeni; C. Tchawoua; P. Woafo
Journal of Sound and Vibration | 2004
F.M. Moukam Kakmeni; Samuel Bowong; C. Tchawoua; Ernest Kaptouom
Chaos Solitons & Fractals | 2004
M. Siewe Siewe; F.M. Moukam Kakmeni; C. Tchawoua
Collaboration
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French Institute for Research in Computer Science and Automation
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