An Improved Method of Equipment Thermal Effect on Command and Control System Based on BPNN and Incremental PID

Constructed incremental PID controller which is based on the BPNN principle and incremental PID temperature control principle. The neural network is trained with 0.1°C resolution and appropriate temperature control error range as sample data, and the weight parameter matrix is obtained. Based on this parameter, the simulation and experimental verification are carried out for large lag nonlinear temperature control, and the experimental results of temperature control error ± 0.2°C are obtained. It is proved that the incremental PID parameter tuning method based on BPNN is feasible in the field of large lag nonlinear temperature precise control.