Current technological advances have brought closer to reality the project of a safe, portable, and efficient artificial pancreas for people with type 1 diabetes (T1D). Among the developed control strategies for T1D, model predictive control (MPC) has been emphasized in literature as a promising control for glucose regulation. However, these control strategies are commonly designed in a computer environment, regardless of the limitations of a portable device. In this paper, the performances of six embedded platforms and three open-source optimization solver algorithms are assessed for T1D treatment. Their advantages and limitations are clarified using four MPC formulations of increasing complexity and a hardware-in-the-loop methodology to evaluate glucose control in virtual adult subjects. The performance comparison includes the execution time, the difference concerning the evolution obtained in MATLAB, the processor temperature, energy consumption, time percentage in normoglycemia, and the number of hypo- and hyperglycemic events. Results show that Quadprog is the package that faithfully follows the results obtained with control strategies designed and tuned on a computer with the MATLAB software. In addition, the Raspberry Pi 3 and the Tinker Board S embedded systems present the appropriate characteristics to be implemented as portable devices in the artificial pancreas application according to the criteria set out in this work.
In recent years, the process carried out in the GACIPE research group is related to the development of the base technology of the manufacturing and metalworking industry. The machine tools that are vital for the consolidation and competitiveness of the industry in any country has been approached through two approaches: The design and construction of the new machine. In this aspect, the modeling of the structure and the displacements’ parameterization allows defining the precision of the movements and the rational use of energy. The adaptation and repowering of a used machine. In this approach, the recovery and technological updating proposed to recover its performance, becoming an excellent alternative to improving and perfecting the production of a company. In both cases, the CNC milling machine tools are controlled by free software. The application proposed is mechanized in soft materials.
An industrial approach to the use of artificial vision is worked, and we are searching for the improvement of the welding process using a robotic arm. These kinds of robots in the last years have been associated to high accuracy tasks like classification, welding, object manipulation, assembly, and so on. Generally, the artificial vision is not used in works which use manipulator arm; this is normally due to the robot programmer who plans the robot task, which is executed cyclically, however, there are some approaches where different tasks using artificial vision are implemented. In this chapter, we present a retrofitting process of a manipulator welder arm Miller MR-2000, and the development of an artificial vision system, which could be used in the positioning of the machine. The developed system is able to look for areas suitable for the welding task between two pieces of material within a workspace; this process is possible using techniques of computational vision and image processing. Subsequently, the algorithm calculates the number of welding points based on the area identified previously, and finally, it sends the respective coordinates by means of G code to the robot for welding the pieces.
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