• 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