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.
MATLAB
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