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In this paper, two methods of control for high-voltage Full Bridge Series-Parallel Resonant (FBSPR) DC-DC converter are proposed and the results are compared. Soft switching operation using Zero Current Switching (ZCS) and Zero Voltage Switching (ZVS) technologies is employed to decrease the losses and optimize the efficiency of converter. The way of obtaining small-signal model of FBSPR converter using the generalized averaging method is discussed. Then two control methods using Artificial Neural Networks (ANN) and Sequential State Machine (SSM) are explained and the experimental results are compared. The ANN controller is trained according to the small signal model of the converter and operating points and the SSM controller operates on base of a finite number of states, actions and functions and determines transition from one state to another according to FBSPR converter conduction status.To compare the performances of two controllers, a prototype is designed and implemented. The prototype is tested for step changes in both output load and reference voltage at steady state and under transient conditions. Comparison between experimental results for both ANN and SSM controllers show better speed performances for SSM controller in small changes in load and more reliability for ANN controller in case of large variations.

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According to this research paper, fuzzy hype plane controller is applied to robust nonlinear controller to reduce the vibration of motor. To control of multi degree of freedom joint, nonlinear controllers are the best candidate. Sliding mode controller is one of the best choices to robust control of this nonlinear system. The sliding mode controller is used to speed up the error convergence when the error is greater than one. To reduce the error terminal sliding mode controller is recommended in this research. Fuzzy hype-plane variable sliding mode controller is adopted to guarantee the error convergence to zero in a finite time when the error is near the zero. The chattering in the conventional sliding model control systems is avoided with the employed continuous controller. To increase the system robustness in presence of uncertainty fuzzy logic controller is recommended. This technique is used to adjust the band of terminals. The simulation results show that the proposed scheme has strong robust against the uncertainties and disturbances, as well as leads to the convergence of the output to the desired value quickly and precisely than employing either sliding mode controller or terminal sliding mode controller alone.

In this paper, we propose a new structure for the plasmonic waveguide to optimize the nonlinear optical effect of the second harmonic generation (SHG). For this purpose, we use a layer of graphene grating and spherical and elliptical plasmon polariton nanoparticles made of gold and silver. The number, location and material of nanoparticles as well as the number of graphene layer gratings are optimized to achieve the highest possible nonlinear effect. The simulation results showed that the optical power of SHF wave and peak optical power of SHF is increased noticeably using grating layer of graphene along with optimized plasmon polariton nanoparticles.