Model of Ball Mill Based on the CPS

[1]Lee J, Bagheri B, Kao H A. A cyber-physical systems architecture for industry 4.0-based manufacturing systems[J]. Manufacturing Letters, 2015, 3: 18-23.10.1016/j.mfglet.2014.12.001Search in Google Scholar

[2]ZHOU Xing-she, YANG Ya-lei, YANG Gang. Modeling methods for dynamic behaviors of cyberphysical system[J]. Chinese Journal of Computers,2014, 37(3): 1Search in Google Scholar

[3]Chen J, Yang J, Zhou H, et al. CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach[J]. Engineering, 2015, 1(2): 247-260.10.15302/J-ENG-2015054Search in Google Scholar

[4]WANG Dong-feng, YU Xi-ning, SONG Zhi-ping. Dynamic mathematical model of ball mill pulverizing system and its inverse control based on distributed neural networks[J]. Proceeding of the CSEE, 2002, 22(1): 97Search in Google Scholar

[5]Yuan Y, Zhang Y, Cao H, et al. Nonlinear prediction model for ventilation of ball mill pulverizing system[C]//Control Conference (CCC), 2016 35th Chinese. TCCT, 2016: 202510.1109/ChiCC.2016.7553664Search in Google Scholar

[6]Mishra B K. A review of computer simulation of tumbling mills by the discrete element method: part I—contact mechanics[J]. International journal of mineral processing, 2003, 71(1): 73-9310.1016/S0301-7516(03)00032-2Search in Google Scholar

[7]MA Tian-yu, GUI Wei-hua. Optimal control for continuous bauxite grinding process in ball-mill[J]. Control Theory & Applications, 2012, 29(010): 1339-1347Search in Google Scholar

[8]LEE E A. Introduction to embedded systems-a cyber-physical systems approach[M]. UC Berkeley, 2014: 79Search in Google Scholar

[9]YU Zhen-hua, CAI Yuan-li, FU Xiao, et al. Formal modeling and analyzing high-confidence software of cyber-physical systems[J]. Systems Engineering theory and practice, 2014, 34(7): 1857Search in Google Scholar

[10]XU Xin, YU Hui-qun, HUANG Jun-hu. Petri net based security quantitative analysis model for cyber-physical system[J] . Computer Engineering and Applications, 2014, 50(3): 82Search in Google Scholar

[11]BANERJEE A, GUPTA S K S. Spatio-temporal hybrid automata for safe cyber-physical systems: a medical case study[C]//2013 ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS). Philadelphia,USA, c2013: 7110.1145/2502524.2502535Search in Google Scholar

[12]Huang G B, Zhu Q Y, Siew C K. Extreme learning machine: a new learning scheme of feedforward neural networks[C]//Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on. IEEE, 2004, 2: 985Search in Google Scholar

[13]Huang G B, Zhou H, Ding X, et al. Extreme learning machine for regression and multiclass classification[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2012, 42(2): 51310.1109/TSMCB.2011.216860421984515Search in Google Scholar