摘要
本文对大量电梯实际运行数据进行分析,将电梯的运行模式分为上行高峰模式、层间交换模式、下行高峰模式和空闲模式等4种情况.根据多模型控制的思想,对不同的交通模式,设计不同权值的评价指标函数,构成多模式自寻优控制器.在多个控制策略的基础上,采用神经网络构成切换机制,给出电梯群控多模型控制器.我们在电梯群控仿真平台上进行了验证,结果显示了本文提出算法的有效性.
Based on the running data of a large number of elevators,the running modes of elevators can be classified into four classes：up-running summit mode,level exchanging mode,down-running summit mode and leisure time mode.According to the idea of multiple-model control,different weights of evaluation index function are designed based on different running modes and multiple self-optimal controllers are developed based on multiple control strategies,and the neural network is employed as the switching mechanism for selecting the appropriate controller for individual elevator.The proposed method is proposed method.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2014年第3期366-374,共9页
Control Theory & Applications
基金
新世纪优秀人才支持计划资助项目(NCET–11–0578)
国家自然科学基金资助项目(61074055)
中央高校基本科研业务费专项资金资助项目(FRF–TP–12–005B)
高等学校博士学科点专项科研基金(博导类)(20130006110008)
关键词
电梯群控系统
自寻优
多模型
elevator group control system
self-optimal
multiple model
