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All Journal Emerging Science Journal Journal of Robotics and Control (JRC)
Moreano, Gabriel
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Environmental Science Mechanical Engineering

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The Role of Immersive Virtual Realities: Enhancing Science Learning in Higher Education Tene, Talia; Guevara, Marco; Moreano, Gabriel; Vera, John; Vacacela Gomez, Cristian
Emerging Science Journal Vol 8 (2024): Special Issue "Current Issues, Trends, and New Ideas in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-SIED1-06

Abstract

Objective: This systematic review aims to map out the role of immersive technologies, specifically virtual and augmented realities (VR and AR), in enhancing learning outcomes within higher education science programs, providing a clearer understanding of their pedagogical value. Methods: Leveraging extensive database searches in Scopus and Web of Science, an initial phase of 172 articles was identified. Through a meticulous process of screening based on inclusion and exclusion criteria, this was refined to 33 important articles. These articles were further analyzed to identify distinct structural elements regarding VR and AR interventions and their effects on educational outcomes. Analysis: Each study was evaluated for its contribution to pedagogical methods, with a focus on quantifiable changes in student performance and engagement. Results: The analysis revealed that immersive technologies are being applied across various stages of the academic crossing, from introductory courses to advanced laboratory work. Particularly, 18 articles demonstrated a significant positive or increased impact on learning outcomes. Conclusions: The review confirms that VR and AR possess a transformative potential for higher education, particularly in the sciences. These technologies not only captivate students' interest but also facilitate deeper understanding and retention of complex material. The evidence suggests that VR and AR can substantially enhance the educational experience when implemented thoughtfully. Future research should aim to expand upon these findings, exploring the longitudinal impact of immersive technologies on learning and their potential to democratize education. Doi: 10.28991/ESJ-2024-SIED1-06 Full Text: PDF
A Novel Fuzzy Identification Approach for Nonlinear Industrial Systems: Eliminating Singularity for Enhanced Control Moreano, Gabriel; Sotelo, Julio Tafur; Andino, Valeria; Villacrés, Sergio; Viscaino, Mayra
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.24241

Abstract

The control of nonlinear systems poses significant challenges due to their inherent complexities, limiting the effectiveness of traditional control strategies. This paper presents an improved fuzzy identification and control method for nonlinear industrial systems, using Takagi-Sugeno fuzzy inference to model nonlinear dynamics as an interpolation of multiple linear subsystems. A key improvement of this approach lies in the accurate identification of the nonlinear model, which leads to fewer control system failures. The research contribution is the development of a control strategy that enhances system reliability while simplifying implementation. The method involves minimizing a cost function that optimizes the system’s output error, refining the fuzzy identification process for dynamic adaptation to varying operating conditions. The strategy also enables the design of linear controllers for each subsystem and applies Parallel Distributed Compensation (PDC) to regulate the overall nonlinear system. This approach is validated through experimental testing on an aero-pendulum system. The results show that the PDCbased control scheme not only ensures high performance across a wide operational range but also significantly reduces identification errors compared to traditional methods. Given its improved accuracy, reduced complexity, and adaptability, this approach holds significant potential for practical application in industrial environments, where robust and efficient control of nonlinear systems is crucial for operational success.
Co-Authors Andino, Valeria Guevara, Marco Sotelo, Julio Tafur Tene, Talia Vacacela Gomez, Cristian Vera, John Villacrés, Sergio Viscaino, Mayra