This paper presents a technology-enhanced, project-based educational framework for teaching intelligent control concepts in engineering curricula. The framework integrates theoretical instruction with computational model-ing and real-time experimentation using a low-cost DC motor platform, ena-bling students to follow the complete control workflow from modeling and simulation to hardware implementation and performance evaluation under realistic non-ideal conditions.

The approach is supported by interactive modeling workflows, MATLAB/Simulink tools, and Live Scripts, and is applied to control prob-lems including proportional-integral-derivative, model predictive, and model reference adaptive control. Representative laboratory case studies illustrate how students implement and experimentally validate their designs on DC motor-based systems and related platforms.

Experimental outcomes and student feedback indicate that the proposed framework improves student engagement and supports the development of practical control skills and conceptual understanding. Overall, the framework provides an accessible and affordable model for intelligent control education, bridging theory and practice through hands-on learning.