DocumentCode :
66697
Title :
Modeling and Simulation of Whole Ball Mill Grinding Plant for Integrated Control
Author :
Shaowen Lu ; Ping Zhou ; Tianyou Chai ; Wei Dai
Author_Institution :
State Key Lab. of Synthetical Autom. for Process Ind., Northeastern Univ., Shenyang, China
Volume :
11
Issue :
4
fYear :
2014
fDate :
Oct. 2014
Firstpage :
1004
Lastpage :
1019
Abstract :
This paper introduces the development and implementation of a ball mill grinding circuit simulator, NEUSimMill. Compared to the existing simulators in this field which focus on process flowsheeting, NEUSimMill is designed to be used for the test and verification of grinding process control system including advanced control system such as integrated control. The simulator implements the dynamic ball mill grinding model which formulates the dynamic responses of the process variables and the product particle size distribution to disturbances and control behaviors as well. First principles models have been used in conjunction with heuristic inference tools such as fuzzy logic and artificial neural networks: giving rise to a hybrid intelligent model which is valid across a large operating range. The model building in the simulator adopts a novel modular-based approach which is made possible by the dynamic sequential solving approach. The simulator can be initiated with connection to a real controller to track the plant state and display in real-time the effect of various changes on the simulated plant. The simulation model and its implementation is verified and validated through a case of application to the design, development, and deployment of optimal setting control system.
Keywords :
control engineering computing; fuzzy control; grinding; neurocontrollers; optimal control; process control; production engineering computing; NEUSimMill ball mill grinding circuit simulator; advanced control system; artificial neural networks; dynamic sequential solving approach; fuzzy logic; grinding process control system; heuristic inference tools; hybrid intelligent model; integrated control; optimal setting control system; process variables; product particle size distribution; whole ball mill grinding plant; Centralized control; Circuit simulation; Intelligent systems; Optimal control; Process control; Control system test-bench; ball mill grinding process; dynamic simulation; grinding process modeling; hardware-in-the-loop simulation; hybrid intelligent modeling; integrated control; optimal setting control; simulation model verification;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2013.2296309
Filename :
6716099
Link To Document :
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