HYBRID INTELLIGENT OPTIMAL-SETTING CONTROL WITH MULTI-OBJECTIVES OF THE RAW SLURRY BLENDING PROCESS IN THE ALUMINA PRODUCTION

Raw slurry blending process is one of the key producing processes in the sintering alumina production. Key technical indices of this blending process are the quality indices of the raw slurry and the load state of the mill. Operation control objectives are to control the quality indices into their targeted ranges and control the load state of the mill in the good state. However, due to the difficulty of measuring the quality indices and the load state on-line, and the complex dynamical characteristics between the technical indices and the control loops, these control objectives are difficult to be realized by using the existing control methods. A hybrid intelligent optimal-setting control of the raw slurry blending process is proposed. The proposed optimal-setting control with the hybrid intelligent approaches can automatically adjust the set-points in order to respond to the variation of the boundary condition. At last, the proposed control approach is applied in an alumina factory in China, and the application results have proven the validity and effectiveness of the proposed methods.