Abstract: The handwriting is a physical demonstration of a
complex cognitive process learnt by man since his childhood. People
with disabilities or suffering from various neurological diseases are
facing so many difficulties resulting from problems located at the
muscle stimuli (EMG) or signals from the brain (EEG) and which
arise at the stage of writing. The handwriting velocity of the same
writer or different writers varies according to different criteria: age,
attitude, mood, writing surface, etc. Therefore, it is interesting to
reconstruct an experimental basis records taking, as primary
reference, the writing speed for different writers which would allow
studying the global system during handwriting process. This paper
deals with a new approach of the handwriting system modeling based
on the velocity criterion through the concepts of artificial neural
networks, precisely the Radial Basis Functions (RBF) neural
networks. The obtained simulation results show a satisfactory
agreement between responses of the developed neural model and the
experimental data for various letters and forms then the efficiency of
the proposed approaches.
Abstract: This paper presents a Particle Swarm Optimization
(PSO) method for determining the optimal parameters of a first-order
controller for TCP/AQM system. The model TCP/AQM is described
by a second-order system with time delay. First, the analytical
approach, based on the D-decomposition method and Lemma of
Kharitonov, is used to determine the stabilizing regions of a firstorder
controller. Second, the optimal parameters of the controller are
obtained by the PSO algorithm. Finally, the proposed method is
implemented in the Network Simulator NS-2 and compared with the
PI controller.
Abstract: This paper proposes a Fuzzy Sliding Mode Control (FSMC) as a control strategy for Buck-Boost DC-DC converter. The proposed fuzzy controller specifies changes in the control signal based on the knowledge of the surface and the surface change to satisfy the sliding mode stability and attraction conditions. The performances of the proposed fuzzy sliding controller are compared to those obtained by a classical sliding mode controller. The satisfactory simulation results show the efficiency of the proposed control law which reduces the chattering phenomenon. Moreover, the obtained results prove the robustness of the proposed control law against variation of the load resistance and the input voltage of the studied converter.
Abstract: This paper deals with the comparison between two proposed control strategies for a DC-DC boost converter. The first control is a classical Sliding Mode Control (SMC) and the second one is a distance based Fuzzy Sliding Mode Control (FSMC). The SMC is an analytical control approach based on the boost mathematical model. However, the FSMC is a non-conventional control approach which does not need the controlled system mathematical model. It needs only the measures of the output voltage to perform the control signal. The obtained simulation results show that the two proposed control methods are robust for the case of load resistance and the input voltage variations. However, the proposed FSMC gives a better step voltage response than the one obtained by the SMC.