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In this paper, a fractional-order version of a chaotic circuit made simply of two non-idealized components operating at high frequency is presented. The fractional-order version of the Hopf bifurcation is found when the bias voltage source and the fractional-order of the system increase. Using Adams-Bashforth-Moulton predictor-corrector scheme, dynamic behaviors are displayed in two complementary types of stability diagrams, namely the two-parameter Lyapunov exponents and the isospike diagrams. The latest being a more fruitful type of stability diagrams based on counting the number of spikes contained in one period of the periodic oscillations. These two complementary types of stability diagrams are reported for the first time in the fractional-order dynamical systems. Furthermore, a new fractional-order adaptive sliding mode controller using a reduced number of control signals was built for the stabilization of a fractional-order complex dynamical network. Two examples are shown on a fractional-order complex dynamical network where the nodes are made of fractional-order two-component circuits. Firstly, we consider an ideal channel, and secondly, a non ideal one. In each case, increasing of the coupling strength leads to the phase transition in the fractional-order complex network.

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At the time when renewable energy is making the headlines, photovoltaic technology has shown significant potential as one of the best energy sources. It is therefore necessary to predict the performance of a photovoltaic system by modeling it accurately and optimally. In this work, we propose a new hybrid algorithm for extracting parameters to improve the performance and the efficiency of a PV cell when subjected to temperature variations. The metaheuristic approach combined with an analytical approach to improve the accuracy and robustness that we call the Improved Differential Evolution (IDE). The performances of the proposed method are evaluated by clicking on cell data. For validation purposes, several analyses and comparisons are made with other methods, and the results illustrate the accuracy and precision of the IDE. The proposed technique is able to estimate the parameters in an optimal way whatever the temperature together with a high convergence speed and a short simulation time.