PIDNN Based Intelligent Control of Ignition Oven

Abstract:

In a steel plant, fuel gas caloricity of ignition oven always changes rapidly and largely. Consequently, the temperature of ignition oven can’t keep steady. To overcome this problem we employ intelligent control of ignition oven based on PIDNN (Proportional-Integral-Derivative Neural Network). As we know, ignition oven is a nonlinear, large delay and slow time-varying process, so traditional PID control usually doesn’t work well. Artificial neural networks can perform adaptive control by learning, so we adopt Proportional-Integral-Derivative neural network to tackle the problem taking the advantages of both PID control and neural structure. In order to satisfy the restrictions of industrial instruments, we combine PIDNN control algorithm with expert system mechanism to fulfill the final intelligent control strategy. At a sintering plant in Hangzhou, we deploy the intelligent control strategy turning out a satisfactory result that the ignition oven temperature can be controlled steadily within a much smaller range with significant saving of labor costs and improving of energy efficiency.

• Periodical: Advanced Materials Research (Volumes 396-398)
• Pages: 493-497
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.396-398.493
• Online since: November 2011
• Authors: Yu Qian Ying, Jian Gang Lu, Jin Shui Chen, You Xian Sun
• Keywords: Intelligent Control, Iron Ore Sintering, PIDNN

References

[1] C.Arbeithuber, H.P. Jörgl and H. Raml, Control Eng. Practice, Vol. 3 (1995), pp.1669-1674

DOI: 10.1016/0967-0661(95)00179-x

[2] Youji Hua. Process Automation Instrument, Vol. 14 (1993), pp.22-25

[3] Hongkui Chen, Qingdong li, HEILONGJIANG YEJIN(In Chinese), Vol. 1 (2007), pp.25-27

[4] Yunxia Song, Xuefeng Zhu, Control and Instruments in Chemical Industry, Vol. 28 (2001), pp.9-15

[5] Joseph Giarratano Gary Riley, Expert Systems Principles and Programming, Course Technology,1-35

[6] Huailin Shu, Computers and Chemical Engineering Vol. 24 (2000), pp.859-862

[7] Xiaoyun Lu, Junyu Hao, Qingdong Zheng, Metallurgical Industry Automation, Vol. 17 (1993), pp.19-23