Neural Network PID Control Strategy

This paper discusses neural network PID control strategy, proposing a single-neuron adaptive PID controller with its control model. It explores the learning algorithm for single-neuron adaptive PID control, constructing an adaptive PID controller by modifying neuron connection weight coefficients. The self-learning capability of neural networks enables online tuning of PID control parameters. MATLAB simulations compare traditional PID controllers with single-neuron adaptive PID controllers, demonstrating that neural network PID controllers offer simplified parameter adjustment, high precision, strong adaptability, and satisfactory control performance.

Fuzzy PID Fuzzy Adaptive PID Controller

Enhanced adaptability for various working conditions with auto-tuning parameter tracking, delivering more rational and precise control. Thoroughly tested through meticulous debugging for automotive engineering, motor control applications and similar domains.