Intelligent optimal setting control of a cobalt removal process

Cobalt removal process is an important step in zinc hydrometallurgy. Because of its complex reaction mechanism and dynamic characteristics, human supervision with low level control is not sufficient to keep the stable and optimal operation of cobalt removal process. This paper presents an intelligent optimal setting control strategy of cobalt removal process. The control strategy consists of process monitoring unit, zinc dust utilization factor (ZDUF) estimation unit, cobalt removal ratio (CRR) optimal setting unit, oxidation reduction potential (ORP) setting unit and case based reasoning (CBR) controller. Process monitoring unit judges the state of current process. When process is at steady state, economical optimization is conducted by allocating suitable CRR to reactors according to their ZDUF. In order to realize automatic control, CRR is transformed into the setting value of ORP through an integrated model which is also able to estimate outlet cobalt ion concentration. When a process is at an abnormal state, case based reasoning controller is triggered to handle the undesired situation by providing rational solution of control variables. An industrial experiment shows that by using the proposed control strategy, zinc dust consumption can be reduced while the required cobalt removal performance is always achieved. Stability of cobalt removal can also be improved by limiting CRR of each reactor in predefined ranges.