About Heating Plants Control System Developing on Basis of Neural Network Usage for PID-Regulator Parameters Optimization

Abstract

An adaptive control system implementation is described. Such system is based on a neural network, used for online PID-regulator coefficients tuning. The backpropagation online training method is used. It is modified by adding a rule base. It contains conditions on choosing neural network learning rate. PID-regulator with neural tuner and conventional PID-regulator were used as regulators during the process of heating furnace control modeling. Such experiments were made for different loading furnace modes and setpoint schedules. The 11% economy of time on setpoint schedule realizing was achieved with the help of proposed neural tuner..