Title :
Hybrid Intelligent System for Supervisory Control of Mineral Grinding Process
Author :
Ding, Jinliang ; Zhou, Ping ; Liu, Changxin ; Chai, Tianyou
Author_Institution :
Res. Center of Autom., Northeastern Univ., Shenyang
Abstract :
The particle size is the important technical performance index of the grinding process, which closely related to the overall performance of the mineral processing. In this paper, we mainly concern on the determination of the particle size for the supervisory control of the grinding process by the technical performance index decision system. The overall structure of the system and introduce of every part are given briefly. The experiment results and its compare with the neural network method show its validity and efficiency
Keywords :
grinding; mineral processing industry; neurocontrollers; performance index; hybrid intelligent system; mineral grinding process; neural network; performance index decision system; supervisory control; Automation; Electrical equipment industry; Hybrid intelligent systems; Laboratories; Minerals; Neural networks; Optimal control; Ores; Performance analysis; Supervisory control;
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.2006.169
