Research On The Control Of The Heating Furnace Based On Neural Network

The heating furnace is a typical large time-delay system, the delay component has an unfavorable impact on the performance of the control system, and even cause the instability of the closed-loop system or cannot makes an effective control on the system. Hence it is always a research difficulty to model and control the time-delay system in the control field.Based on the prevalence study of the heating furnace control, the article discusses the technical difficulties in the control of heating furnace. The main research contents are as follows:1. According to the large time-delay system of heating furnace, the characteristics of general PID control, cascade control and Smith prediction control in the control of heating furnace system are studied.2 We studied the function of combination algorithms of neural networks and Smith prediction control and PID control in the control processes of heating furnace.3. Focuses on the pure time-delay system, we propose a control strategy based on neural network compensation and achieve the combination of Smith prediction control and neural network control using Smith prediction control theory and the ability of neural network which can approximate nonlinear function arbitrarily. Simulation results show that the algorithm not only has good control effects but also can improve the robustness and the control performance of the system.