A PID Control Tuning Method Based on BP Neural Network

This MATLAB source program implements PID control parameter tuning through BP neural networks. The algorithm utilizes neural network learning and training capabilities to dynamically optimize PID controller parameters (proportional, integral, and derivative gains) for achieving more precise and stable control performance. The implementation includes key functions for neural network initialization, forward propagation calculations, and backpropagation weight updates. The code structure features modular components for: - Neural network architecture configuration (input/hidden/output layers) - PID parameter adjustment logic based on network outputs - Real-time control error minimization through gradient descent optimization Through this source code, users can easily implement BP neural network-based PID control within the MATLAB environment, providing enhanced control system performance with adaptive tuning capabilities. The program demonstrates practical integration of artificial intelligence techniques with classical control theory for improved system response and stability.