Title :
Decoupling Control for Electrode System in Electric Arc Furnace based on Neural Network Inverse Identification
Author_Institution :
Sch. of Electr. Engineering & Inf., Anhui Univ. of Technol., Ma´anshan
Abstract :
RBF neural network based on nearest neighbor clustering algorithm is applied for three-phase electrode system in electric arc furnace. Real-time on-line decoupling of MIMO inverse system is realized, and transfers MIMO system with strong coupling into individual pseudo linear plant. On the base of these, the method dealing linear system can be used for the pseudo linear system. The simulation and experiments indicate that this strategy is suitable for engineering
Keywords :
MIMO systems; arc furnaces; electrodes; identification; linear systems; pattern clustering; radial basis function networks; real-time systems; MIMO inverse system; RBF neural network; decoupling control; electric arc furnace; electrode system; inverse dynamic identification; method dealing linear system; nearest neighbor clustering algorithm; neural network inverse identification; pseudo linear plant; pseudo linear system; real-time on-line decoupling; Artificial neural networks; Control systems; Delay effects; Electrodes; Furnaces; Inverse problems; Linear systems; MIMO; Neural networks; Real time systems; RBFN; electrode system in electric arc furnace; inverse dynamic identification; on-line decoupling; pseudo linear plant;
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
DOI :
10.1109/ISDA.2006.253815
