In this paper, experimental results about the performance of a Takagi–Sugeno Fuzzy Controller (TSFC) for an EV3 Ballbot Robotic System (EV3BRS) are reported. The physical configuration of the EV3BRS has the form of an inverted pendulum mounted on a ball. The EV3BRS is an underactuated robotic system with four outputs and two control torques. In this work, following the Takagi–Sugeno (TS) fuzzy control design methodology, the Parallel Distributed Compensation (PDC) approach is used in the design of the TSFC. The EV3BRS’s TS Fuzzy Model (TSFM) design comes from linearization of the nonlinear model around two operation points near the upright position of EV3BRS’s body. The Linear Matrix Inequality (LMI) approach was used to obtain the feedback gains for every local linear controller, guaranteeing, via a conservative stability condition, the global asymptotic stability of the overall fuzzy control system. The main goal of the control task consists of maintaining the EV3BRS’s body at its upright position. Measurement and control data from and to the EV3BRS are transferred via telecontrol and telemetry. The appropriate performance of the controller design is corroborated via experimentation.

In this paper, experimental results about the performance of a Takagi-Sugeno Fuzzy Controller (TSFC) for an EV3 Ballbot Robotic System (EV3BRS) are reported. The physical configuration for the EV3BRS has the form of an inverted pendulum mounted on a ball. The EV3BRS is an underactuated robotic system with four outputs and two control torques. The Takagi-Sugeno Fuzzy Model (TSFM) design comes from linearization of the nonlinear model around two operation points near from the upright position of the EV3BRS's body. The Parallel Distributed Compensation (PDC) approach is used to the design of the TSFC. The Linear Matrix Inequalities (LMIs) approach is used to get the feedback gains for every local linear controller guaranteeing global asymptotically stability, via a more relaxed stability condition, of the overall fuzzy control system. Measurement and control data from and to the EV3BRS are transferred via telecontrol and telemetry.

Nowadays, various systems were developed in the telecommunications field which make use of technologies for the transmission and reception of information. One of these technologies is the Internet, which was developed in tandem with scientific growth. Therefore, its application in the control of various industrial processes has a notable influence. In this context, there are industrial processes that, due to the potential danger they represent to human beings, must be controlled by means of a remote control system. Such systems can be implemented through client–server communication schemes, which form a network of computers to exchange information. In the exchange of information, delay times are generated. These inactivity times have a close relationship with the latency in the communication network and have a negative impact on the performance of closed-loop control systems. In this sense, for physical implementation, it is essential to measure and mathematically characterize their magnitudes in order to know their variability and thus be able to design control strategies that compensate for their effects. Hence, this research paper presents the reconstruction of the communication times measured from a telecontrol system, where it is assumed that only one subsystem acts as the controller and the other one acts as the controlled. In other words, this paper addresses a control scheme type of single-input-single-output system (SISO). This reconstruction is based on the Kalman filter, which estimates the communication times that are measured on an experimental test bench with a client–server communication scheme. Communication times are characterized as stochastic processes. So, in order to validate the reconstruction presented, the level of dependence between the random processes is evaluated by analyzing their moments of probability as well as their covariance moments. Finally, an analysis based on the mean square error is presented, through which it can be concluded that the reconstruction technique used allows one to know the dynamics of the communication times generated by the remote control process presented in this research.

Municipal Solid Waste (MSW) is a common problem in all cities worldwide; it is expected to increase to 3400 billion tons by 2050. In Mexico, an average of 108,146 tons of MSW are generated daily. Artificial Intelligence (AI) is a computer tool that allows the development of systems that facilitate the recycling process. However, most AI programs focus on classifying paper, plastic, glass and metal; therefore, wood and textile waste have received little attention. Using texture techniques such as Local Binary Pattern (LBP), Gray-Level Co-occurrence Matrix (GLCM), Histogram of Oriented Gradients (HOG), Canny/Sobel edge detection, Fractal Dimension (FD), feature values were extracted and integrated from 4396 images belonging to wood and textile categories. Using the Random Forest Importance method, the most significant features were selected to train three Machine Learning (ML) algorithms. Multilayer Perceptron (MLP) achieved the best performance in accuracy with 96.70%, followed by Random Forest (RF) at 95.45% and Support Vector Machine (SVM) with 95.22%. The implementation of these comparisons will serve as a basis for the development of new technological tools with low computational cost that carry out a proper waste separation.

Based on their technological competencies, students must develop projects based on an integral methodology that responds to real problems with empathy and a sustainable vision so that, at the end of their studies, they can become entrepreneurs and generate jobs, or else technology transfer could occur. This methodology has been developed and tested at the Emiliano Zapata Technological University of the State of Morelos (UTEZ) with the support of experts from other Higher Education Institutions (HEI) since 2016, maturing through developing and improving selected prototypes aligned with strategic areas. This methodology was developed by integrating various existing strategies, techniques, and tools entrepreneurs use to provide students with tools and experiences that allow them to carry out technology-based entrepreneurship at the end of their studies since employment opportunities are generally scarce. This methodology has fostered learning activities that are participatory and interactive based on STEAM among students. It supports the formation of creative and empowered engineers capable of working in collaborative teams. The results obtained from participation in various innovation contests and competitions validate the methodology, which has enabled the student teams to receive awards and recognitions at the national and international levels. Previously, this type of participation was incipient. However, a tremendous pending step is the transfer of technology.

Actualmente existe un gran interés en el desarrollo de máquinas que atiendan la demanda para rehabilitar las extremidades superiores e inferiores, debido a lesiones provocadas por enfermedad vascular cerebral, accidentes traumáticos, enfermedades neuromusculares, que día a día van en aumento. El objetivo de este trabajo es presentar el análisis cinemático de una máquina de rehabilitación de miembros superiores para pacientes que han sufrido una enfermedad vascular cerebral. La máquina de rehabilitación es de tres grados de libertad (GDL), utiliza un cable flexible y puede proporcionar movimientos del hombro de: flexión-extensión, rotación externa y abducción; y movimiento de flexión del codo, entre otros. Se presenta el análisis cinemático de algunos movimientos básicos que puede proporcionar esta máquina mediante el análisis de un lazo vectorial. Además, los resultados de la simulación en el entorno de MSC Adams muestran que la máquina de rehabilitación puede proporcionar movimientos de rehabilitación pasivos suaves.