Stochastic optimization for real-time operation of alumina blending process. (December 2020)

• Record Type: Journal Article
• Authors: Kong, Lingshuang; Yin, Yanyan; Yang, Chunhua; Gui, Weihua; Teo, Kok Lay
• Is Part Of: Journal of process control. Volume 96(2020)
• Page Start: 49
• Page End: 56
• Publication Date: 2020-12
• Subjects: Stochastic optimization -- Sample selection approach -- Alumina production -- Blending process -- Real-time operational control -- Uncertainties; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2020.10.005
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: In this paper, the stochastic optimization blending operation is applied to the alumina production in this paper. A new binomial distribution based stochastic scenario optimization used together with the sample selection approach is utilized to design the optimal set point for control, under which the probability of quality indices of the raw slurry being within the tolerance region is high enough in the presence of uncertainties caused by fluctuation of the raw material and disturbances. Through practical industrial experiments, it is observed that the proposed stochastic optimization method is effective and the computational cost is low. Highlights: Optimal operation of alumina blending process is solved as an optimization problem. The resulting indices in raw materials are all within the expected tolerance. The industrial experiment shows that the results posse better robustness.