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.

自从发表了开创性的模糊集论文以来，许多研究生和本科学术课程都将模糊逻辑课程作为人工智能 (AI) 方面最重要的主题之一。然而，值得强调的是，人工智能作为教育工具的主要根源在于向学生教授人工智能的方式，导致许多教育模式的发展，寻求加速模糊逻辑概念的学习曲线及其适用性用于控制系统。尽管如此，这些方法中的大多数主要集中在理论概念上，而没有提高通过实验挑战发展起来的学科和横向能力；因此，知识获取是不完整的，工业要求没有得到满足。今后，这项工作提出了一个受系统开发 V 模型启发的模型，该模型允许学生通过实验产品开发过程了解整个模糊逻辑控制器设计过程，从而提高学生的终身学习特征。此外，该模型支持学生的基于挑战的学习 (CBL)，鼓励模糊逻辑控制器设计的新技能开发和经验积累。此外，本文提出的方法论涵盖了适用于教育的 V 模型，以通过 Quadcopter 案例研究了解模糊逻辑控制器的设计过程，由于系统的复杂性而选择，（结果支持）也有助于提高工程专业学生的背景技能。所以，结果表明，该模型提高了学生开发功能原型的能力，促进了技术产品的开发。然后，通过工程技术领域内的专家评审委员会的验证，该提案可以很容易地适用于多个工程主题；例如，电子电路设计，电力电子等。