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作 者:高军 刘亚东 GAO Jun;LIU Ya-dong(Neusoft Corporation,Shenyang 110819,China;College of Information Science and Engineering,Northeastern University,Shenyang 110819,China)
机构地区:[1]东软集团股份有限公司,辽宁沈阳110819 [2]东北大学信息科学与工程学院,辽宁沈阳110819
出 处:《长春师范大学学报》2022年第10期65-73,共9页Journal of Changchun Normal University
基 金:国家自然科学基金项目“定量信息与定性信息共同驱动的流程工业过程运行状态评价及智能决策”(61873053)。
摘 要:在黄金湿法冶炼生产过程中,由于不确定变量影响引起的某些子过程无法建立其定量模型,使得传统优化方法难以实现基于模型优化求解。本文构建了一种基于定性定量混合建模的区间优化求解框架。首先,基于现场操作人员经验等信息,建立了压滤脱水调浆过程的模糊定性模型,通过结合两阶段氰化浸出过程的定量模型,进而获得一个有效的过程混合优化模型。其次,不确定性变量由区间数描述,并划分为多个模态。通过采用基于区间数的过程优化求解方法,将不确定性条件下的过程优化模型转化为等价的确定性优化模型。最后,采用仿真实验测试算法的性能。与传统的过程优化方法相比,本文提出的方法能够充分体现过程决策的灵活性,在具有不确定性的流程工业生产过程优化中具有一定的应用价值。During the gold hydrometallurgy process, due to the effect of uncertain variables, the quantitative model of some subprocesses cannot be established, which makes it difficult to achieve model-based optimization by using the traditional optimization methods. In this paper, a framework of interval optimization based on the qualitative and quantitative hybrid modeling is proposed. Firstly, based on the experience of field operators, the fuzzy qualitative model of the pressure filtration dewatering and pulp mixing process is established to achieve an effective optimization model by combining with the quantitative models of two-stage cyanidation leaching processes. Moreover, the uncertain variables are handled by interval number and are divided into multiple modes. By using the optimization solution method based on the interval number, the process optimization model under the condition of uncertainties is transformed into an equivalent deterministic formulation. Finally, the performance is tested by simulation experiments. By comparing with the traditional process optimization methods, the proposed method can fully reflect the flexibility of the process design, and has a certain application value in the optimization of process industry with uncertainty.
关 键 词:湿法冶金 区间优化 模糊定性模型 粒子群优化 不确定性理论
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程]
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