The number and position of sEMG electrodes have been studied extensively due to the need to improve the accuracy of the classification they carry out of the intention of movement. Nevertheless, increasing the number of channels used for this classification often increases their processing time as well. This research work contributes with a comparison of the classification accuracy based on the different number of sEMG signal channels (one to four) placed in the right lower limb of healthy subjects. The analysis is performed using Mean Absolute Values, Zero Crossings, Waveform Length, and Slope Sign Changes; these characteristics comprise the feature vector. The algorithm used for the classification is the Support Vector Machine after applying a Principal Component Analysis to the features. The results show that it is possible to reach more than 90% of classification accuracy by using 4 or 3 channels. Moreover, the difference obtained with 500 and 1000 samples, with 2, 3 and 4 channels, is not higher than 5%, which means that increasing the number of channels does not guarantee 100% precision in the classification.

Electric vehicles (EVs) are an alternative to internal combustion engine (ICE) cars, as they can reduce the environmental impact of transportation. The bottleneck for EVs is the high-voltage battery pack, which utilizes most of the space and increases the weight of the vehicle. Currently, the main challenge for the electronics industry is the cell equalization of the battery pack. This paper gives an overview of the research works related to battery equalizer circuits (BECs) used in EV applications. Several simulations were carried out for the main BEC topologies with the same initial conditions. The results obtained were used to perform a quantitative analysis between these schemes. Moreover, this review highlights important issues, challenges, variables and parameters associated with the battery pack equalizers and provides recommendations for future investigations. We think that this work will lead to an increase in efforts on the development of an advanced BEC for EV applications.

Most robot controllers are proprietary and, therefore, they have a closed architecture, and it is typical for robot vendors not to provide support for old control units; hence, when a deprecated robot requires an update or even a simple preventive maintenance, the manufacturer tends to recommend disposing such a unit and to acquire a new one. In this paper, the development of a field programmable gate array-based motion control system is described as part of an open-architecture and vendor-independent control system tested on a Fanuc S420F. As a way to measure the performance of the developed system, an experimental test is carried out to achieve a path tracking RMS error lower than 20 mm at a Cartesian velocity of 500 mm/s. Results demonstrate that the proposed system achieves the same feed rates as the original controller with the significant advantage of being modular, flexible, scalable, and reconfigurable.

Nowadays, there are several techniques for the acceleration and deceleration of computer numerical control (CNC) machine tools and industrial robots (Robot manipulators) in order to plan smoother trajectories avoiding the jerk and another kind of stress. The aim of this article is to show a comparison between the trapezoidal and s-curve velocity profile used in robotics and CNC machinery. After doing that, the reader will be able to select a velocity profile in order to design their trajectories.

A proper charge in an electric vehicle (EV) battery allows it to have a longer useful life and lower maintenance costs. For this purpose, the voltage and current supplied to the battery must be precisely regulated. In this article, the model of a phase-shifted full-bridge (PSFB) converter is obtained. Moreover, a dual control loop was designed to regulate the state of charge of a lithium ferrofosfate (LiFePO${}_4$) battery. The autoregressive exogenous (ARX) model is used to model the system. Once the plant model is obtained, it is controlled using a classical controller. A couple of cases are evaluated where the control parameters are modified, and the best approach is selected. From the obtained model, the controller is designed for the proposed cases. The theoretical controller response is compared with the experimental response. The results show a 94% accuracy of the model. In the same way, the result obtained from the controller is accurate in a 96% by comparing it with a simulation. Both the modeling and the control obtained experimentally resemble the results obtained theoretically. The controller manages to respond as expected in all proposed cases.

This paper presents a robot motion controller for an undergraduate laboratory study program. It is designed to help the students learn and to assess specific learning outcomes proposed by ABET by solving a real‐life problem. The main objective of this project is to enable the engineering students to learn some core concepts about embedded systems and motion controllers for robotics by applying them in practice. Also, the proposal shows how to introduce the students to a new tendency in the embedded system market, namely, an All Programmable System on a Chip (SoC). This methodology incorporates interdisciplinary knowledge, technical and professional skills required for pursuing a successful career. In the present study, we surveyed the observations and interests of students towards the learning process, and the results indicate that the inclusion of the robot prototype has a significant impact on providing students with new learning outcomes.