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Research On Elevator Group Control System Based On The Time Ladder Optimal Algorithm

Posted on:2019-01-06Degree:MasterType:Thesis
Country:ChinaCandidate:Q LiuFull Text:PDF
GTID:2382330563990623Subject:Control engineering
Abstract/Summary:PDF Full Text Request
Elevator as an indispensable means of transportation in the building has been accompanied by the emergence of new algorithms,new technologies,new ideas,and constantly upgrade,provides better quality and convenient service for people.The traditional elevator group control system has such problems as single control target,poor adaptability and low energy saving effect.The Multi-objective programming theory and the different intelligent control algorithms are combined to realize the optimal scheduling control of the elevator group control system.Aiming at the defects of single control target in traditional algorithm,an elevator group control algorithm based on Multi-objective programming has been proposed,which is based on 3 factors: comprehensive time,passenger satisfaction and energy consumption.In order to reduce the time and reduce energy consumption,4 evaluation indexes are defined,and the comprehensive optimal scheduling under the evaluation index is realized.In view of the complexity of the elevator group control system.It has many fuzzy variables,the control model can not be set up accurately by mathematical method,an elevator group control algorithm based on Fuzzy Control has been proposed.The corresponding relationship between input and output is established by fuzzy inference.It solves the problem that fuzzy variables can not accurately establish mathematical models.By comparing and evaluating the function value,the operation of the elevator is realized.Fuzzy control and Neural Network are combined to solve the problem that the traffic environment has been changing and the fuzzy rules are limited.Establish the controlled model of the elevator group control system through Fuzzy Control.Build up the nonlinear relation between input and output through BP Neural Network,through its self-learning to adjust the weights,thus optimize the relationship between input and output and make the system adapt to the change of traffic environment.In order to shorten the time and reduce the energy consumption as the main purpose,using 3 algorithms to realize elevator group control system scheduling.The 3 algorithms,to varying degrees,reduce the passenger's long time ladder rate and the number of elevator stops,thus solve the problem of single target and much energy consumption in traditional control algorithm,and realize the energy saving optimization of the elevator group control system.
Keywords/Search Tags:elevator group control system, energy saving optimization, Multi-objective programming, Fuzzy Control, Fuzzy Neural Network
PDF Full Text Request
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