2017
DOI: 10.1021/acs.iecr.6b04801
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Abstract: The gold cyanidation leaching process (GCLP) has been prevalent in the hydrometallurgical industry. To better control and optimize the plant operation, mechanistic models have been established which capture the physical behaviors of the GCLP. However, due to various disturbances and uncertainties, an optimized operation based on the nominal model is practically suboptimal. To perform real-time optimization (RTO) of the GCLP, this paper proposes a two-layer control architecture integrating the self-optimizing c… Show more

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Cited by 20 publications
(10 citation statements)
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“…Generally, the GCLP is operated manually in a heuristic way, and excessive cyanide is added to guarantee the recovery of the gold product. 5 Due to the increasing global market competition, the incentive to reduce the economic cost of the GCLP is becoming more and more important. In addition, excessive addition of cyanide will have a great adverse effect on the environment.…”
Section: Introductionmentioning
confidence: 99%
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“…Generally, the GCLP is operated manually in a heuristic way, and excessive cyanide is added to guarantee the recovery of the gold product. 5 Due to the increasing global market competition, the incentive to reduce the economic cost of the GCLP is becoming more and more important. In addition, excessive addition of cyanide will have a great adverse effect on the environment.…”
Section: Introductionmentioning
confidence: 99%
“…Although the reaction rates were estimated by dynamic historical data in their work, only a steady-state optimization problem was formulated to compute the optimal process set-points. To further deal with the disturbances in GCLP, self-optimizing control (SOC) algorithm is adopted by Ye et al 5 as a supervisory controller in a two-layer control architecture to maintain the process operations at the optimal set-points. However, the two-layer architecture means that the controller is designed without considering the transient costs explicitly.…”
Section: Introductionmentioning
confidence: 99%
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“…Ye [34] developed a controlled variable adaptation-based structure to improve the optimizing performance. A two-layer control architecture integrating the SOC and modifier adaptation (MA) was also provided by Ye [35] to address the plant-model mismatch.…”
Section: Introductionmentioning
confidence: 99%
“…Through using actual measured value and gradient information to correct the original optimization problem, the iterative result can converge to the optimal set‐point of the actual process . Due to various disturbances and uncertainties, Ye et al establish a two‐layer control architecture integrating the self‐optimizing control and modifier adaptation to better control and optimize the GCLP plant operation . For the optimization problem under fuzzy uncertainty for the copper removal process of zinc hydrometallurgy, Zhang et al propose a method based on fuzzy rules to estimate the process conditions .…”
Section: Introductionmentioning
confidence: 99%