A microsystem design for controlling a DC motor by pulse width modulation using MicroBlaze soft-core

This paper proposes a microsystem based on the field programmable gate arrays (FPGA) electronic board. The preliminary objective is to manipulate a programming language to achieve a control part capable of controlling the speed of electric actuators, such as direct current (DC) motors. The method proposed in this work is to control the speed of the DC motor by a purely embedded architecture within the FPGA in order to reduce the space occupied by the circuit to a minimum and to ensure the reliability of the system. The implementation of this system allows the embedded MicroBlaze processor to be installed side by side with its memory blocks provided by Xilinx very high-speed integrated circuit (VHSIC) hardware description language (VHDL), Embedded C. The control signal of digital pulse-width modulation pulses is generated by an embedded block managed by the same processor. This potential application is demonstrated by experimental simulation on the Vertix5 FPGA chip

Design and Implementation Intelligent Adaptive Front-lighting System of Automobile using Digital Technology on Arduino Board

The automatic light AFS (Adaptive Front - Lighting System) is added to the capabilities of modern vehicles that will improve the safety of vehicle drivers and passengers traveling at night. A new architecture of the AFS has proposed in this paper. This architecture is powerful and intelligent using the PWM technique on ARDUINO Board replaces the old mechanical system based on stepper motors

A New Photovoltaic Blocks Mutualization System For Micro-Grids Using An Arduino Board And Labview

The photovoltaic systems are often employed into micro-grids; Micro-grids are small power grids designed to provide a reliable and better power supply to a small number of consumers using renewable energy sources.This paper deals with DC micro-grids and present a new system of monitoring and sharing electricity between homes equipped with photovoltaic panels (PV) in the goal to reduce the electrical energy waste. The system is based on dynamic sharing of photovoltaic blocks through homes in stand-alone areas, using an arduino board for controlling the switching matrix. The LABVIEW program is used to further process and display collected data from the system in the PC screen. A small-scale prototype has been developed in a laboratory to proof the concept. This prototype demonstrates the feasibility and functionality of the system

Three-dimensional phenotype characteristics of skeletal class III malocclusion in adult Chinese: a principal component analysis–based cluster analysis

Background: Skeletal class III malocclusion has a diverse and complicated aetiology involving environmental and genetic factors. It is critical to correctly classify and define this malocclusion to be diagnosed and treated on a clinically sound basis. Thus, this study aimed to provide reliable and detailed measurements in a large ethnically homogeneous sample of Chinese adults to generate an adequate phenotypic clustering model to identify and describe the skeletal variation present in skeletal class III malocclusion. Materials and methods: This is a retrospective cross-sectional study in which 500 pre-treatments cone-beam computed tomography (CBCT) scans of patients with skeletal class III malocclusion (250 males and 250 females) were selected following specific selection criteria. Seventy-six linear, angular, and ratios measurements were three-dimensionally analysed using InVivo 6.0.3 software. These measurements were categorised into 47 skeletal, 18 dentoalveolar, and 11 soft tissue variables. Multivariate reduction methods: principal component analyses and cluster analyses were used to present the most common phenotypic groupings of skeletal class III malocclusion in Han ethnic group of Chinese adults. Results: The principal component analysis revealed eight principal components accounted for 72.9% of the overall variation of the data produced from the seventy-six variables. The first four principal components accounted for 53.37% of the total variations. They explained the most variation in data and consisted mainly of anteroposterior and vertical skeletal relationships. The cluster analysis identified four phenotypes of skeletal class III malocclusion: C1, 34%; C2, 11.4%; C3, 26.4%; and C4, 28.2%. Conclusion: Based on three-dimensional analyses, four skeletal class III malocclusion distinct phenotypic variations were defined in a large sample of the adult Chinese population, showing the occurrence of phenotypic variation between identified clusters in the same ethnic group. These findings might serve as a foundation for accurate diagnosis and treatment planning of each cluster and future genetic studies to determine the causative gene(s) of each cluster.This work was supported by the project of the National Natural Science Foundation of Gansu Province, China (No. 20JR5RA264)