This paper introduces a new soft-switched high gain converter topology with Input Current Smoother (ICS) capability to mitigate Normalized Peak Inverse Voltage (NPIV). By employing soft switching techniques, the converter achieves significant reductions in switching losses and improved overall efficiency, making it ideal for high-frequency applications. The proposed converter enhances voltage gain while minimizing voltage stress on power semiconductors, overcoming the limitations of conventional step-up converters. The paper provides a detailed description of the converter's operation principles, configuration, and steady-state analysis. Performance comparisons with existing topologies demonstrate superior voltage gain, minimized voltage stress on semiconductors, negligible input current ripple, and remarkable efficiency. Finally, simulation results demonstrate the advantages of the proposed converter by using PSCAD software.

Voltage spikes during the switching transients play an important role in determining the power losses in hard-switching converters. These spikes are functions of several factors at the instant of switching such as DC-link voltage, load current, transistor and diode switching delay times, reverse recovery current of the diode, parasitic capacitance and inductance of the circuit. This paper introduces a numerical approach to accurately model the switching power losses of a single-phase H-bridge (SPHB) inverter. The data required to obtain the equivalent resistance is extracted from the experimental double-pulse tests (DPTs). Then, the concept of local and global rms currents is considered to incorporate the effect of pulse width modulation (PWM) in the estimation of the switching losses. The results are computed for unipolar and bipolar PWM schemes. Finally, the reflection rule is utilized to obtain an equivalent output resistance for the inverter switching losses.

Finite Control Set Model Predictive Control appears an interesting and effective control technique for Cascaded H-Bridge converters but, because of its computational complexity, becomes impractical when the number of levels of the converter increases. This paper proposes a Neural Network-based approach capable of overcoming the computational burden of conventional predictive control algorithms. The proposed control is then applied to a Cascaded H-Bridge Static Synchronous Compensator using FPGA and tested via hardware in the loop. Results and analysis demonstrate that optimal control of multilevel converters with many levels can be obtained with low computational effort.

Finite Control Set Model Predictive Control is an effective technique which attracted attention in the latest years thanks to its fast dynamic response and the fact that it does not require a modulation. However, when applied to multilevel converters, it requires a large amount of calculations that may affect implementability. On the other hand, Neural Networks are well known Machine Learning techniques that can be efficiently implemented in real-time applications thanks to their massive parallelism capability. This work proposes a novel Finite Control Set Model Predictive Control approach based on Neural Networks with reduced computational time complexity for a Cascaded H-Bridge Static Synchronous Compensator. Simulation results for a nine-level system are presented and a simulative comparison between our approach and classical methods for FCS is provided, showing that very similar performance can be achieved with strong reduction of the computational complexity.

This paper develops, within a general framework that is applicable to rather arbitrary electromagnetic and acoustic remote sensing systems, a theory of time-reversal "MUltiple Signal Classification" (MUSIC)-based imaging of extended (nonpoint-like) scatterers (targets). The general analysis applies to arbitrary remote sensing geometry and sheds light onto how the singular system of the scattering matrix relates to the geometrical and propagation characteristics of the entire transmitter-target-receiver system and how to use this effect for imaging. All the developments are derived within exact scattering theory which includes multiple scattering effects. The derived time-reversal MUSIC methods include both interior sampling, as well as exterior sampling (or enclosure) approaches. For presentation simplicity, particular attention is given to the time-harmonic case where the informational wave modes employed for target interrogation are purely spatial, but the corresponding generalization to broadband fields is also given. This paper includes computer simulations illustrating the derived theory and algorithms.