ժҪ On the background of the bright continuous simulative annealing experimental machine, the process control model of heating system is built in the paper. The heating model was simplified and the self-learning parameter was normalized in the paper in order to enhance the precision of the temperature control. By way of dividing temperature layers and exponential smoothing disposal with the data of the annealing experiment, self-learning of heating model was carried out, and at the same time, by way of exponential smoothing with the deviation of self-learning parameter of the heated phase in heating process, dynamic modifying of self-learning parameter was carried out, and so that dynamic modifying of heating electric current was carried out, and so, the precision of temperature control was confirmed. Application indicates that the process control model of heating system can control temperature with high precision, the deviation can be controlled in 8��,it can offer reference to the research of similar equipments, and the method of self-learning is also adapt to process control of cooling system
Abstract��On the background of the bright continuous simulative annealing experimental machine, the process control model of heating system is built in the paper. The heating model was simplified and the self-learning parameter was normalized in the paper in order to enhance the precision of the temperature control. By way of dividing temperature layers and exponential smoothing disposal with the data of the annealing experiment, self-learning of heating model was carried out, and at the same time, by way of exponential smoothing with the deviation of self-learning parameter of the heated phase in heating process, dynamic modifying of self-learning parameter was carried out, and so that dynamic modifying of heating electric current was carried out, and so, the precision of temperature control was confirmed. Application indicates that the process control model of heating system can control temperature with high precision, the deviation can be controlled in 8��,it can offer reference to the research of similar equipments, and the method of self-learning is also adapt to process control of cooling system
WANG Yun-hua;et al. Application of Self-learning to Heating Process Control of Simulated Continuous Annealing[J]. �й������ڿ���, 2010, 17(6): 27-31.
WANG Yun-hua;et al. Application of Self-learning to Heating Process Control of Simulated Continuous Annealing. Chinese Journal of Iron and Steel, 2010, 17(6): 27-31.
2010, Vol. 17 
