A novel approach to controlling brushed DC motors using neural networks, overcoming the limitations of traditional PID controllers. This project explores the potential of neural networks to learn and adapt to the complexities of model train control, achieving smooth and stable motion.

Demonstrate on-device training of a neural network using AIfES Library on an ESP32 board, learning the XOR gate function.