Stimulating Higher Order Thinking in Mechatronics by Comparing PID and Fuzzy Control

Overview

This study addresses limitations in traditional active learning approaches that fail to develop higher order thinking skills corresponding to the upper levels of Bloom's Taxonomy. The research documents the design and implementation of an open-ended project in a mechatronics course requiring students to compare proportional-integral-derivative (PID) and fuzzy control methodologies for autonomous leader-follower vehicle behavior. Unlike conventional assignments with prescribed procedures and solutions, this project deliberately omits explicit performance criteria and experimental protocols, compelling students to engage in analysis, synthesis, and evaluation. The pedagogical intervention responds to the observation that professional engineering practice demands facility with complex, ambiguous problems requiring design decisions without straightforward answers, yet undergraduate engineering education often relies on structured problems that do not cultivate these capabilities.

Methods and approach

The project was structured as the culminating activity in a semester-long mechatronics course, with preparatory laboratory exercises distributed throughout the term to establish requisite technical competencies. These preliminary exercises covered sensor and actuator integration, programming of both PID and fuzzy controllers, and computer vision techniques for object signature detection. The final project required students to determine which control methodology performs superiorly for autonomous vehicle following behavior. Critically, students were not provided with predetermined performance metrics or experimental procedures. Instead, they were tasked with independently developing evaluation criteria and designing comparative experiments. The approach was implemented across three academic semesters, allowing for iterative observation of student responses and outcomes.

Results

Implementation across three semesters yielded several consistent findings regarding student engagement and cognitive development. Students demonstrated appreciation for confronting real-world, open-ended problems that lack predetermined solutions. The evaluation criteria and experimental methodologies developed by students exhibited creativity and reflected engagement with higher order thinking skills, particularly in the domains of analysis, synthesis, and evaluation as defined by Bloom's Taxonomy. Students recognized through direct experience that comparative studies of control methodologies involve nontrivial complexity due to the multiplicity of factors affecting performance. This recognition represents a departure from expectations conditioned by more structured academic problems and aligns more closely with the ambiguity characteristic of professional engineering decision-making.

Implications

The findings suggest that deliberate removal of prescriptive elements from engineering projects can effectively stimulate higher order cognitive processes that are underutilized in conventional active learning implementations. The approach demonstrates that open-ended comparative tasks requiring student-generated evaluation frameworks can bridge the gap between structured academic exercises and the ill-defined problems encountered in professional practice. The methodology presents a replicable framework for engineering education seeking to develop analytical and evaluative capabilities beyond implementation of known solutions. The study contributes to understanding how curricular design choices influence cognitive skill development, particularly regarding the transition from procedural competence to independent engineering judgment. The recognition by students that comparative studies are nontrivial represents an important metacognitive outcome that may influence their approach to future engineering problems requiring comparative analysis and design decision-making under uncertainty.

Disclosure

• Research title: Stimulating Higher Order Thinking in Mechatronics by Comparing PID and Fuzzy Control
• Authors: Christopher J. Lowrance, John R. Rogers
• Publication date: 2026-01-10
• DOI: https://doi.org/10.48550/arxiv.2601.08865
• OpenAlex record: View
• Image credit: Photo by mwitt1337 on Pixabay (Source • License)
• Disclosure: This post was generated by artificial intelligence. The original authors did not write or review this post.