Nowadays, there is a need to increase the continuous usage of the power electronic converters like AC-DC, DC-DC, and DC-AC based on various applications like mobile charge controller and telecom base station. Also, for power stability control, these converters are utilized in the renewable energy system (RES). The output cannot be stable for a longer duration due to the inappropriate switching pulse and continued usage of the converter. For resolving the above issues, the soft-switching technique is implemented in the proposed system for controlling both converter and inverter for proper energy stabilization during the continuous operation of devices. The main objective of this work is to improve the solar power system using high voltage gain DC / DC converter. Similarly, an inverter delivers the continuous AC power to the grid system without any fluctuations. The revolutionary substantial transformative control (RSTC) technique has been employed to monitor and control the converters used in this system. The additional advantage of this system is battery-based energy management, which is only utilized under necessary conditions. During the initial stage, RSTC will track the solar power, and it compares with the reference voltage and produces the appropriate pulse to the converter switch. Based on the switching pulse, the full-bridge converter (FBC) will also enhance the DC voltage by providing the constant voltage for the grid-connected inverter system. Secondly, the proposed RSTC controller will be monitoring voltage amplitude and frequency of grid power system. If any variation appears due to source power fluctuation, the controller will recognize it and automatically vary the pulse width modulation (PWM) of an inverter and compensate the grid power. The design analysis and operating approaches of the proposed converter are verified by MATLAB / Simulink 2017b. The performance analysis has been done with various parameters like total harmonics distortion (THD), steady-state error and converter efficiency.

Design and operation of a compiler and virtual machine, being the essential components of a multiplatform control programming environment, are presented. The compiler translates source programs written in Structured Text language of the IEC 61131-3 standard into executable code in a dedicated intermediate language. The virtual machine, i.e. a specially designed processor implemented in software, is a runtime part of the environment executing the code in real time. Due to memory-to-memory operation principle the machine is able to process various data types defined in the standard. The focus is given on overloading and extensibility of the functions, as well as on uniform invocations of Program Organization Units. By selection of addressing mode, the environment can be deployed on multiple hardware platforms, beginning from 8-bit microcontrollers up to 32/64-bit industrial PCs. Industrial applications are indicated.

This paper develops an automatic method to calculate the macrotexture depth of pavement roads, using the tire/road noise data collected by the two directional microphones mounted underneath a moving test vehicle. The directional microphones collect valid tire/road noise signal at the travel speed of 10–110 km/h, and the sampling frequency is 50 kHz. The tire/road noise signal carries significant amount of road surface information, such as macrotexture depth. Using bandpass filter, principal component analysis, speed effect elimination, Gaussian mixture model, and reversible jump Markov Chain Monte Carlo, the macrotexture depth of pavement roads can be calculated from the tire/road noise data, automatically and efficiently. Compared to the macrotexture depth results by the sand-patch method and laser profiler, the acoustic method has been successfully demonstrated in engineering applications for the accurate results of macrotexture depth with excellent repeatability, at the test vehicle’s travel speed of 10-110 km/h.

In order to achieve higher frequency measurement accuracy, this paper proposed a characteristic pulse detection method of fuzzy area based on the quantized phase processing method of different frequency groups. First, the fuzzy area of the group phase coincidence points continuously moved on the time axis after passing through delay elements. The moving distance, that is, the number of the delay elements was determined by the main clock cycle of the D flip-flop. After that, three groups of phase coincidence detection fuzzy areas in different positions were sent to the digital logic module to extract the edge pulses of the phase coincidence detection fuzzy area. The pulse width is determined by the difference between the clock cycles of the delay elements. The clock cycles of different delay units were adjusted to obtain nanosecond or even picosecond circuit detection resolution. Finally, the pulses generated at the edge of the phase coincidence fuzzy area are taken as the switching signal of the frequency signal counter, so the stability of the gate signal and the accuracy of the gate time measurement are improved. The experimental results show that frequency stability can reach the order of E-13/s. In addition, compared with the traditional measurement method, it is characterized by simple structure, low cost, low noises, and high measurement resolution.