Study on Neural Network Self-Tuning PID Control for Temperature of Active Solar House Heating System

Aiming at temperature of active solar house heating system ,which has a non-linear, large time-delay, time-varying and model uncertain characteristics , to solve the problem, neural network self-tuning PID control algorithm is proposed. The algorithm takes the advantages of PID control algorithm for system adaptability and robustness, and has advantages of self-learning ability and adjusting the weights automatically in neural network for achieving perfect control effect on time-varying, noise disturbance characteristics of the parameters. Simulation results show that the algorithm has an effective suppression of non-linear, time-varying and time delay for the heating system, effectively improving the control accuracy and system adaptability for winning perfect control of the active solar house.