化工学报2017，Vol.68Issue(9)：3511-3521,11.DOI:10.11949/j.issn.0438-1157.20170583
混合多目标骨干粒子群优化算法在污水处理过程优化控制中的应用
Optimal control of wastewater treatment process using hybrid multi-objective barebones particle swarm optimization algorithm
摘要
Abstract
Through analysis of biological wastewater treatment process (WWTP), a multi-objective optimal control strategy was developed with targets of minimizing both energy consumption and amercement. A hybrid multi-objective barebones particle swarm optimization (HBBMOPSO) algorithm based on Pareto dominance and decomposition was proposed to improve convergence and diversity of optimized set of Pareto solutions. In HBBMOPSO, selection of personal leaders was determined from self-adaptive penalty factor decomposition while maintenance of external dossiers and selection of global leaders were determined from dominance and crowded distance. Furthermore, elitism learning strategy was adopted to facilitate particle escaping from local Pareto fronts. Finally, HBBMOPSO was combined with self-organizing fuzzy nerve network modeler and controller to realize dynamic optimization, intelligent decision, and background monitoring on dissolved oxygen and nitrate nitrogen in biological WWTP. Experimental study on international standardized simulator platform BSM1 showed that HBBMOPSO method can effectively reduce energy consumption under the premise of ensuring effluent to meet quality standard.关键词
污水/优化/过程控制/粒子群/分解Key words
wastewater/optimization/process control/particle swarm/decomposition分类
信息技术与安全科学引用本文复制引用
周红标,乔俊飞..混合多目标骨干粒子群优化算法在污水处理过程优化控制中的应用[J].化工学报,2017,68(9):3511-3521,11.基金项目
国家自然科学基金重点项目(61533002).supported by the State Key Program of National Natural Science Foundation of China (61533002). （61533002）
