摘要
针对城市污水处理难于实现高品质控制的问题,探讨了GAPSO算法在污水曝气控制器参数优选中的应用,分析了污水曝气DO参数的控制难点,并采用新提出的改进GAPSO算法,在已有控制策略基础上优化了控制器参数,同时该算法也优化了多模态的智能控制器参数.以二阶滞后过程为控制对象,采用GAPSO算法优化控制参数后进行仿真实验.仿真结果表明:该算法对控制参数的优化实现了较高的控制品质,在控制器参数优化方面效果显著.
In order to improve the control quality of municipal sewage treatment, this paper explored the application of improved PSO algorithm in controller parameter optimization of sewage aeration process, also analyzed the control puzzle of DO parameter in sewage aeration. Then it adopted a proposed new and improved GAPSO algorithm, which had made the optimization of controller parameter based on the existed control strategy, and at the same time, the algorithm optimized the parameter of multi-modal intelligent controller. By setting the sewage treatment with lag as the control object, the paper adopted the GAPSO algorithm to optimize the control parameters before the simulation research, which demonstrated that the optimized control parameters with the algorithm could get a high control quality. The improved algorithm have achieve a remarkable effect on parameters optimization of controllers, and it have a certain theoretical significance.
出处
《辽宁工程技术大学学报（自然科学版）》
CAS
北大核心
2016年第7期776-780,共5页
Journal of Liaoning Technical University (Natural Science)
基金
重庆市教委科学技术研究项目(KJ102102)
关键词
粒子群算法
仿人智能控制
SBR法
溶解氧浓度
污水处理
particle swarm optimization algorithm
human-simulated intelligent control
method of SBR
dissolved oxygen concentration
sewage treatment
