Title :
Modelling of the raw mixing process in cement industry
Author :
Özsoy, Can ; Kural, Ayhan ; Baykara, Cemal
Author_Institution :
Mech. Fac., Istanbul Tech. Univ., Turkey
Abstract :
This paper represents the identification of a raw blending system in a cement factory for advanced process control. Three different linear multivariable stochastic ARX (AutoRegressive with eXogenous input) models are proposed in which the inputs are the feed rates of the raw material components (low-grade limestone and iron ore) and the outputs are the iron oxide and/or lime module of the raw meal. The ARX models are parameterized giving the minimum number of parameters by the approach of R.P. Guidorzi (1975). The identification results show that these MISO and MIMO models are good models.
Keywords :
MIMO systems; autoregressive processes; blending; cement industry; cements (building materials); identification; iron; process control; CaCO/sub 3/; CaO; Fe; Fe/sub 3/O/sub 4/; FeO; MIMO models; MISO models; advanced process control; autoregressive models; cement industry; exogenous input; iron ore; linear multivariable stochastic ARX models; low-grade limestone; minimum parameter number; model parameterization; raw blending system identification; raw material component feed rates; raw meal; raw mixing process modelling; Adaptive control; Cement industry; Control systems; Feeds; Iron; Kilns; MIMO; Production facilities; Raw materials; Stochastic systems;
Conference_Titel :
Emerging Technologies and Factory Automation, 2001. Proceedings. 2001 8th IEEE International Conference on
Conference_Location :
Antibes-Juan les Pins, France
Print_ISBN :
0-7803-7241-7
DOI :
10.1109/ETFA.2001.996404
