This research focused on developing a methodology that facilitates the learning of control engineering students, specifically developing skills to design a complete control loop using fuzzy logic. The plant for this control loop is a direct current motor, one of the most common actuators used by educational and professional engineers. The research was carried out on a platform developed by a group of students. Although the learning techniques for the design and implementation of controllers are extensive, there has been a delay in teaching techniques that are relatively new compared to conventional control techniques. Then, the hands-on laboratory offers a tool for students to acquire the necessary skills in driver tuning. In addition to the study of complete systems, the ability to work in a team is developed, a fundamental skill in the professional industrial area. A qualitative and quantitative analysis of student learning was carried out, integrating a multidisciplinary project based on modern tools.

Performing control is necessary for processes where a variable needs to be regulated. Even though conventional techniques are widely preferred for their implementation, they present limitations in systems in which the parameters vary over time, which is why methods that use artificial intelligence algorithms have been developed to improve the results given by the controller. This work focuses on implementing a position controller based on fuzzy logic in a real platform that consists of the base of a 3D printer, the direct current motor that modifies the position in this base, the power stage and the acquisition card. The contribution of this work is the use of genetic algorithms to optimize the values of the membership functions in the fuzzification of the input variables to the controller. Four scenarios were analyzed, in which the trajectory and the weight of the system were modified. The results obtained in the experimentation show that the rising and setting times of the proposed controller are better than those obtained by similar techniques that were previously developed in the literature. It was also verified that the proposed technique reached the desired values even when the initial conditions in the system changed.

Post-consumer polymers require viable actions to transfer value to the final consumer to reduce environmental impact. Worldwide, initiatives are being developed to promote the culture of recycling and thus reduce waste generation. These initiatives seek to make the work of thousands of people visible, encourage job creation, and promote businesses through incentive schemes for effective separation, collection, classification, reuse, and recycling, in the hands of consumers, collectors, and scavenges. It is necessary to emphasize that Mexico needs to develop techniques to increase the productivity of collection centers for recyclable materials and to face the challenges that recycling implies. For these reasons, the Mexican government has spoken of waste management as a national priority due to the COVID-19 pandemic, which increased urban solid waste between 3.3 % and 16.5 % in addition to what was generated under normal conditions. Also, the recycling chain provides economic income to more than 35 thousand Mexicans. Polyethylene terephthalate (PET) is an example of the most notable circular economy in Mexico because 60 % of PET bottles are recycled. Therefore, this article addresses the methods and systems in the management of urban solid waste. It focuses on post-consumer recycled plastic bottles to provide an overview of cost-effective strategies for designing and developing an affordable sorting system in Mexico from the academic field. In addition, to simplify the solution that we propose, it is recommended to combine optical techniques such as infrared spectroscopy and Raman spectroscopy with others methods that work together, such as computer vision, to develop affordable systems that address the limitations of mechanical systems.