DESIGN AND FABRICATION OF A COST-EFFECTIVE NEURAL-FUZZY SEPARATELY EXCITED DC MOTOR SPEED CONTROL TRAINING MODULE

Abstract

The significance of electric drive control in modern engineering is considerable, with notable applications in electric vehicle drives and industrial and domestic automation process control. As technology continues to advance, the need for the development of efficient, interactive, and cost-effective training modules for electric drive controllers is becoming increasingly important. Although the use of online laboratories has been reported to have positive outcomes in the training of students, the practical applicability of the training is restricted. The training module can be used to carry out various machine laboratory experiments. e.g., Dynamic Stress Test in an adaptive neuro-fuzzy inference system (ANFIS), characteristic of a separately excited direct current (DC) motor, and AI-driven control-signal control experiments, not to mention just a few. This study presents the design, development, and implementation of an effective, interactive, and cost-effective training module. It uses ANFIS to control the speed of a direct current motor, with MATLAB/Simulink for controller training and a Raspberry Pi for implementation. A comparative analysis of the ANFIS-based controller with traditional Proportional-Integral controllers under varying load conditions was conducted. It was validated to achieve an impressive transient response with a settling time of 0.80 seconds and a percentage overshoot of only 1.2%. This optimised controller was then implemented on the physical module, which was successfully built with a total Bill of Materials of $315.50. Testing under a physical load disturbance confirmed that the ANFIS controller outperformed, achieving a measurable 33.33% reduction in steady-state error from 4.5 rpm to 3.0 rpm compared to a traditional, well-tuned PI controller. This work provides a complete, validated, and open-design plan for a high-performance intelligent control engineering educational tool that enables effective, hands-on engineering education at a much more affordable cost than commercial and industrial alternatives on the market.