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Plant‐wide optimization for gold hydrometallurgy based on the fuzzy qualitative model and interval number
Author(s) -
Liu Yadong,
Chang Yuqing,
Niu Dapeng,
Wang Fuli
Publication year - 2018
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.3077
Subject(s) - hydrometallurgy , interval (graph theory) , process (computing) , mathematical optimization , fuzzy logic , key (lock) , computer science , process engineering , engineering , mathematics , artificial intelligence , computer security , combinatorics , chemical engineering , dissolution , operating system
Since the difficulty of obtaining accurate online‐measurement of some key variables in hydrometallurgy plant‐wide production process causes that the quantitative models of some procedures are difficult to establish and the plant‐wide optimization based on quantitative model is difficult to realize, a plant‐wide optimization method based on interval numbers is proposed in this work. First, based on the information of expert knowledge and the experience of field workers, a fuzzy qualitative model is constructed, and outputs of the qualitative model are reasonably divided into multiple modes simultaneously. By analyzing the process properties, an optimal control problem for hydrometallurgy plant‐wide production process in the steady state is proposed to achieve process requirements which is to obtain the lowest cost of sodium cyanide and zinc as well as high gold quality. Then, by using interval numbers to represent the key variables that cannot be measured, an optimization method based on interval numbers is proposed for every output mode of the qualitative model. Finally, the hydrometallurgy process is carried in industrial simulation experiment. The results demonstrate that the proposed optimization scheme has much wider applicability than conventional optimization methods, especially for its improved performance of solving optimization problem with uncertainty.