Determination of supercapacitor parameters based on fractional differential equations

In this paper, we estimate the parameter values of a fractional-order model of supercapacitors involving fractional derivatives of Liouville-Caputo, Caputo-Fabrizio, and Atangana-Baleanu and fractional conformable derivative in the Liouville-Caputo sense. We present the exact solution of the considered model using the properties of the Laplace transform operator together with the convolution theorem. They developed numerical simulations using each one of the fractional derivatives; the results were compared graphically with experimental data obtained from different supercapacitors using standard laboratory equipment. The nonlocal parameters involved in the equivalent electrical circuit for the supercapacitor model are recalculated for each fractional derivative using a particle swarm optimization algorithm for generating optimal solutions.     

Trajectory tracking control based on non-singular fractional derivatives for the PUMA 560 robot arm

Multibody System Dynamics - The use of principal points and principal vectors in the formulation of the equations of motion of a general 4R planar four-bar linkage is shown with two kinds of...     

AC Conductivity and Dielectric Response of Polycrystalline and Amorphous C70

The AC conductivity and dielectric constant of polycrystalline and amorphous C₇₀ samples were measured in the 75-300 K temperature range and in the 100 Hz to 1 MHz frequency range. For polycrystalline samples, we observe effects caused by O₂ intercalation due to prolonged exposure to ambient air. The conductivity σ of these samples around 300 K depends on the measuring frequency ν as a σ ∼ νⁿ with n ≈ 0.88, implying a strong reduction of DC conductivity to less than 10^-12 S/cm. The dielectric constant of polycrystalline samples shows an anomaly at 285 K which is interpreted as due to the transition from its intermediate rhombohedral phase into its monoclinic low-temperature phase. In contrast with the polycrystalline samples, the amorphous C₇₀ samples prepared by sublimation do not contain interstitial 0₂, their conductivity at 300 K is of about 10^-6 S/cm, is independent of frequency, and is well described by the hopping mechanism (Davis-Mott T^1/4 law) in the 200-300 K range. All evidence of phase transitions disappears in the amorphous samples.     

Fractal-fractional neuro-adaptive method for system identification

Engineering with Computers - Neuronal networks are used in different fields of science and technology due to their capacity to approximate nonlinear functions through the synaptic weights...     

Experimental implementation of a control scheme to feed a hydrogen-enriched E10 blend to an internal combustion engine

In this work, a control scheme formulation for the injection of a hydrogen-enriched E10 blend (10% of ethanol and 90% of gasoline) in an internal combustion (IC) spark-ignition (SI) engine is presented, the proposed scheme was experimentally tested. The hydrogen was produced on-demand by an electrolyzer. It is considered that only 8% of the overall air entering through the throttle valve reacts with the hydrogen gas, maintaining the hydrogen-air stoichiometric ratio at 34.3. To regulate the hydrogen gas production, the feed current to the electrolyzer was controlled by a feedback PI controller. The dosage of the E10 blend was controlled by the injection timing according to the air-E10 stoichiometric ratio (14.04). Using the hydrogen-enriched E10 blend the resulting air-fuel stoichiometric ratio in the exhaust gas emission was 14.8. The experimental results showed that the E10 blend consumption was reduced. In addition, the thermal and combustion efficiencies were increased and the braking power was not reduced.     

On the trajectory tracking control for an SCARA robot manipulator in a fractional model driven by induction motors with PSO tuning

This paper describes the fractional modeling and control of an industrial selective compliant assembly robot arm (SCARA); the fractional model was obtained by using the Euler–Lagrange and Hamilton formalisms. Each joint of the robot manipulator was driven by an induction motor. In this work, the fractional model of each induction motor was formulated, and the matching of the induction motors with the SCARA robot is shown. For comparison purposes, the SCARA robot control was formulated by conventional PI and PD and by fractional PI ^? and PD ^δ controllers. So each induction motor was controlled by using PI and fractional PI ^? controllers, and for trajectory tracking control, PD and fractional PD ^δ controllers were designed. For tuning the PI, PI ^? , PD, and PD ^δ controllers, the PSO algorithm was used; the same restrictions were used for the PI and PD classical controllers, and ITAE index was used as a cost function to be minimized. For computing the fractional derivatives and to obtain the numerical solution of the system, the Riemann–Liouville and Grünwald–Letnikov approaches were used. The numerical simulations have shown the effectiveness of the use of fractional PI ^? and PD ^δ controllers.