Proceedings of the
The Nineteenth International Conference on Computational Intelligence and Security (CIS 2023)
December 1 – 4, 2023, Haikou, China
Multi-Zone Temperature Decoupling Control System Based on Fuzzy Neural Network PID Algorithm
College of electrical and power engineering, Taiyuan University of Technology, China.
ABSTRACT
The multi-zone temperature control system of electric heating furnace has some defects, such as nonlinear, hysteresis and strong coupling. This paper introduces the principle of a multi-zone temperature control system for electric heating furnace. Aiming at the problem that the traditional PID has a poor control effect on the electric heating furnace, a multi-zone decoupling control method of fuzzy neural network PID is proposed. Firstly, the temperature transfer function model of the electric heating furnace is identified, and the pre-feedback compensation decoupling is used to eliminate the coupling effect between the multi-zone temperatures. The PID parameters of the temperature control system are optimized by a fuzzy neural network control algorithm. Finally, the test was carried out based on actual engineering data, simulink model was built to compare the traditional PID and fuzzy neural network PID through simulation analysis. Results show that after joining the decoupling control of a fuzzy neural network PID control algorithm in the overshoot and adjustment time and other performance indicators are better than the other two kinds of control algorithm. In the meantime, eliminating coupling effects in the multi-temperature zone, to realize the precise control of temperature in the multi-temperature zone of the electric heating furnace.
Keywords: Electric heating furnace, Multi-temperature zone, Fuzzy neural network, Pre-feedback compensation decoupling.
Download PDF
College of electrical and power engineering, Taiyuan University of Technology, China.
ABSTRACT
The multi-zone temperature control system of electric heating furnace has some defects, such as nonlinear, hysteresis and strong coupling. This paper introduces the principle of a multi-zone temperature control system for electric heating furnace. Aiming at the problem that the traditional PID has a poor control effect on the electric heating furnace, a multi-zone decoupling control method of fuzzy neural network PID is proposed. Firstly, the temperature transfer function model of the electric heating furnace is identified, and the pre-feedback compensation decoupling is used to eliminate the coupling effect between the multi-zone temperatures. The PID parameters of the temperature control system are optimized by a fuzzy neural network control algorithm. Finally, the test was carried out based on actual engineering data, simulink model was built to compare the traditional PID and fuzzy neural network PID through simulation analysis. Results show that after joining the decoupling control of a fuzzy neural network PID control algorithm in the overshoot and adjustment time and other performance indicators are better than the other two kinds of control algorithm. In the meantime, eliminating coupling effects in the multi-temperature zone, to realize the precise control of temperature in the multi-temperature zone of the electric heating furnace.
Keywords: Electric heating furnace, Multi-temperature zone, Fuzzy neural network, Pre-feedback compensation decoupling.
Download PDF