Title :
An adaptive control system of flatness for tandem cold mill
Author :
Tan Shubin ; Shen Shaokui ; Liu Jianchang ; Yu Xia
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
Flatness is an important quality of the steel strip, and the flatness control is the key technology of modern rolling mills with high precision of flatness. Taking the adaptive flatness control system of tandem cold rolling mill as the research object, based on some theoretical research and simulation analysis on the adaptive flatness executing system control system, a Self-tuning control strategy based on BP neural network was designed, which can overcomes the disadvantage influence brought in by nonlinearity in use of neural networks. Due to join the adaptive mechanism, it can effectively solve the negative influence of the model change and environmental disturbance. Consequently, the dynamic performance of the flatness control system is improved.
Keywords :
adaptive control; backpropagation; cold rolling; control nonlinearities; control system synthesis; neurocontrollers; performance index; quality control; rolling mills; self-adjusting systems; sheet metal processing; spatial variables control; steel; BP neural network; adaptive flatness control system; adaptive flatness executing system control system; adaptive mechanism; control design; control nonlinearity; dynamic performance improvement; environmental disturbance; flatness precision; model change; self-tuning control strategy; simulation analysis; steel strip quality; tandem cold mill; tandem cold rolling mill; Adaptation models; Artificial neural networks; Control systems; Mathematical model; Strips; Vectors; adaptive control; neural Network; self-turning control; strip flatness;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
