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.

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.

This article aims to enhance technological advancements in the classification of polyethylene terephthalate (PET) bottle plastic, positively impacting sustainable development and providing effective solutions for collection centers (CC) in Mexico. Three experimental designs and machine learning tools for data processing were developed. The experiments considered three factors: bottle size, liquid volume, and bottle labels. The first experiment focused on determining the sensor distance from post-consumer PET bottles. The second experiment aimed to evaluate the sensor’s detection ability with varying liquid levels, while the third experiment assessed its detection capability for bottle labels. A digital lux meter integrated with a microcontroller was developed to monitor illuminance in post-consumer PET bottles containing liquid as they moved through a conveyor belt at an average rate of three bottles per second. The implemented methodology successfully detected liquids inside transparent PET bottles when they contained beverages ranging from 25% to 100% of their capacity. This study highlights the feasibility of implementing an affordable design for identifying bottles with liquids at CC.

This article seeks to strengthen efforts in technological developments based on the classification of PET plastic that positively impacts sustainable development and contributes to suitable solutions in collection centers in Mexico. Three experiment designs and machine learning tools for data processing were developed. For the experimentation, three factors were considered: the bottle's size, the amount of liquids inside the bottle, and the label on the bottle. The first experiment was to identify the distance of the sensor from post-consumer PET bottles. The second experiment was to determine the detection ability of the sensor with different levels of liquids inside the bottles, and the third was to determine the detection ability on the bottle labels. A digital lux meter on a microcontroller was developed to monitor illuminance on post-consumer PET plastic when it contains liquid as it passes through a conveyor belt for processing at an average rate of three bottles per second. With the implemented methodology, liquids were satisfactorily detected inside the transparent PET bottles when they had beverages between 25% and 100% of their capacity. Finally, this paper highlights that it is possible to implement an affordable design to identify bottles with liquids for collection centers.