Teaching fuzzy controllers through a V-model based methodology

Abstract

Since the seminal fuzzy sets paper was published, many graduate and undergraduate academic programs have included Fuzzy logic courses, as one of the most important topics regarding Artificial Intelligence (AI). Yet, it is worth highlighting the fact that AI as a tool for education has its main roots in the way AI is taught to students, leading to the development of many educational models, seeking to accelerate the learning curve of fuzzy logic concepts and their suitability for control systems. Nevertheless, most of those methodologies are mainly focused on theoretical concepts, without improving disciplinary and transversal competences that are developed through experimental challenges; consequently, knowledge acquisition is incomplete, and the industrial requirements are not fulfilled. Henceforth, this work proposes a model inspired by the Systems Development V-Model, which allows students to understand the entire fuzzy logic controllers design process through an experimental product development process that improves lifelong learning features in students. Besides, this model supports the Challenge-Based Learning (CBL) in students, encouraging new skills development and experience gain for fuzzy logic controllers designs. Moreover, the proposed methodology in this paper, covers the adapted V-model for education to understand the designing process for fuzzy logic controllers, through a Quadcopter case study, selected due to the complexity of the system, which (as supported from the results) also leads to improve the background skills in engineering students. Therefore, results show that this model enhances student’s capacity to develop functional prototypes and promotes technological products development. Then, as validated through an expert review committee within the engineering technical field, this proposal could be easily suited into several engineering topics; such as, Electronic circuits design, Power electronics and so on.