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Stringent environmental regulations and increasing oil prices showcase the need for renewable energy sources like solar in marine transportation. The application of solar energy in electric propulsion systems is growing tremendously. Power electronics-based inverters help in harvesting direct current (DC) power into alternating current (AC) power. A multilevel inverter (MLI) is a popular power electronic converter producing the desired output voltage from several DC input voltage sources like batteries, supercapacitors, and solar panels. An MLI consists of several switches whose action results in severe harmonic issues. Specific harmonic elimination in MLI is a challenging job and is resolved conventionally by the Newton-Raphson method. However, nowadays, soft computing techniques are used to solve nonlinear equations optimally. In this manuscript, minimization of total harmonic distortion in MLI has been taken as an optimization problem and is solved using teaching-learning‐based optimization (TLBO). The TLBO algorithm is applied to compute the optimum switching angles for MLI to produce the required fundamental output voltage with less harmonic distortion. As it does not require any algorithm-specific parameters, TLBO is an effective method to obtain optimum MLI solutions. A 21-level symmetric MLI is simulated and is used to evaluate the performance of the TLBO algorithm. The simulation results are validated using an experimental model of proposed MLI with a Xilinx Spartan-SA field programmable gate array‐based controller. This research outcome bears testimony to TLBO optimization's efficiency in improving the quality of the power generated in ships using renewable sources.

Unmanned Aerial Vehicles (UAVs) technology is one of the fastest growing technologies nowadays and is deployed in various fields. UAVs are used in many domains such as surveillance, precision agriculture, mapping and surveying, militaries etc. UAVs can move fast, it can enable the user to look past walls and fences, and it provides a large aerial view of the area where the drone flies. UAVs can also be used to harness information from dangerous places to prevent human casualties. These advantages of UAVs allow us to use Unmanned Aerial Vehicles in many fields. This paper proposes a prototype of an automatic artillery system that can get GPS coordinates of a target location based on the intelligence provided by an Unmanned Aerial Vehicle which spots the location of the target easily. The artillery system can be used to eject a projectile and make it fall on the target position. This system has applications like riot control in urban cities. It can also be used by police or military personnel to take control over terrorist infested areas without manually entering into the region of terror. This UAV directed artillery system is a very viable, cost efficient and effective when compared to conventional methods to control riots and counter terrorists. This system enhances peace in cities and ensures safety and security of the people.

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Maximizing solar energy harvesting and miniaturizing DC-to-DC converters will be a difficult task for the CubeSat that operates in low earth orbit (LEO), where size and weight are limited. To maximize solar energy collection, the electrical power system (EPS) architectures use numerous separate DC–DC converters, which will be problem for miniaturization of whole model because several inductors will be used in each converter. The key purpose of this article is to demonstrate a topology of multiport converter that requires only one inductor and a small number of components, reducing the overall system size. The proposed system will have half-bridge modules with series connection, connected parallelly with PV panels will power the battery system through a DC-DC boost converter. On considering the 1U CubeSat standards a prototype is used to verify the performance of the proposed converter in numerous case scenarios.