基于遗传算法的连续碳酸化分解过程模糊优化  

FUZZY OPTIMIZATION FOR THE PROCESS OF CONTINUOUS CARBONATION DECOMPOSITION BASED ON GENETIC ALGORITHM

作　　者：胡志坤[1] 阳春华[1] 桂卫华[1] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083

出　　处：《金属材料与冶金工程》2007年第5期34-37,共4页Metal Materials and Metallurgy Engineering

基　　金：国家973计划(2002cb312200);国家自然科学基金资助项目(60574030);湖南省自然科学基金(06FD007)

摘　　要：提出了基于遗传算法的连续碳酸化分解过程操作模式模糊优化方法。首先建立基于模糊规则和模糊推理的模型,然后以稳态误差为优化目标,应用混合编码的遗传算法同时优化模糊控制隶属度和推理规则,将获得的模糊规则应用于末槽分解率的控制,获得了良好的应用效果。A fuzzy optimization method based on genetic algorithm for the operational process of continuous carbonation decomposition was proposed. First establishing the control model including fuzzy rules and fuzzy induction, afterwards with the steady state error acting as optimum target, and membership functions and fuzzy reference rules were optimized by a novel genetic algorithms, which had characteristics of hybrid lengthvarying coding scheme. This fuzzy rules were applied to control the resolution ratio of last cell, and results showed that it was practical.

关 键 词：连续碳酸化分解 模糊规则 分解率 遗传算法 

分 类 号：TQ133.1[化学工程—无机化工]