Hybrid intelligent optimising control for high-intensity magnetic separating process of hematite ore

Hybrid intelligent optimizing control method for high intensity magnetic separating process of hematite ore was investigated. The method was based on CBR and RBR to control the concentration grade and the tailing grade within their respective range of target value. Case based reasoning (CBR) technology was combined with the experiment. CBR model consists of five component, which are case production, case retrieval, the case reuse, the case revision, and the case retain. A protocol analysis method together with the experts experiments for the operation of high intensity magnetic separator was adopted in the RBR based feedback compensator. The optimal control method was applied to the Hematite ore concentrating factory. It was concluded that optimal setting layer is composed by a CBR based setting model and a RBR based pre set points feedback compensator and loop control layers tracks both concentration grade and tailing grade.