This review paper introduces the modeling, measurement, identification and control of direct current motors based on the state space modeling and the transfer function representation. These models are identified by real laboratory measurements, and the simulated results are compared with the measurements. Continuous-time and discrete-time PID (Proportional-Integral-Derivative) controllers, discrete-time state feedback and linear quadratic controllers are designed mathematically. The designed controllers are realized by the microcontroller Arduino UNO, and the behavior of the controllers is compared and analyzed. The noisy current signal has been measured by a discrete-time observer, steady-state Kalman filtering is also studied. The practical results of the implemented controllers support the theoretical results very well.

This research investigates the application of plastic fiber reinforcement in pre-tensioned reinforced concrete railway sleepers, conducting an in-depth examination in both experimental and computational aspects. Utilizing 3-point bending tests and the GOM ARAMIS system for Digital Image Correlation, this study meticulously evaluates the structural responses and crack development in conventional and plastic fiber-reinforced sleepers under varying bending moments. Complementing these tests, the investigation employs ABAQUS’ advanced finite element modeling to enhance the analysis, ensuring precise calibration and validation of the numerical models. This dual approach comprehensively explains the mechanical behavior differences and stresses within the examined structures. The incorporation of plastic fibers not only demonstrates a significant improvement in mechanical strength and crack resistance but paves the way for advancements in railway sleeper technology. By shedding light on the enhanced durability and performance of reinforced concrete structures, this study makes a significant contribution to civil engineering materials science, highlighting the potential for innovative material applications in the construction industry.

This study examines the use of Unmanned Aerial Vehicles (UAVs) in transportation, focusing on traffic monitoring and accident prevention. UAVs provide a cost-effective means for traffic surveillance, route planning, and accident analysis, enhancing data accuracy and timeliness. The paper discusses autonomous and human-intervention-supported drone systems for traffic surveillance, addressing technological and operational challenges and the balance needed for practical implementation. It also presents recent advancements, including a forerunner drone model, and references research on UAVs for maritime navigation safety, underscoring the need for their safe and efficient integration into transportation systems.

The accurate measurement and modeling of ferromagnetic material losses are vital issues during the design and analysis of electrical machines. Higher loss values can describe the manufactured rotor and stator machine plates better than the catalog data obtained by standardized measurements using the Epstein frame. In this paper, different temperature-dependent models based on the loss-separation principle are introduced and compared with the measurements. The model parameters are computed from customized laboratory and standardized measurements. The customized measurements based on the stator part of an induction machine in the range of the automotive industry standard, i.e., in [−40 $°$C, ⋯, 180 $°$C]. The proposed model and measurement process can be used in the post-processing stage of numerical field analysis to obtain electromagnetic losses according to the agreement between measured and simulated results. During a numerically expensive optimization process, this model can be used to consider the temperature dependence of the losses more accurately. The study shows that more than 50% of loss increase can be measured, compared with the catalog data, if we use the manufactured, stator-based, customized measurements based on the estimation of the iron loss parameters.