Destination registration elevator group control system modeling and dispatching policy in peak traffic pattern

2008 ◽  
Author(s):  
Xu Yuge ◽  
Luo Fei ◽  
Yang Hong
Keyword(s):  
Control System ◽  
System Modeling ◽  
Traffic Pattern ◽  
Group Control ◽  
Elevator Group Control

The Scheduling of the Elevator Group Control System Modeling and Simulation Based on PSO

2012 ◽  
Vol 229-231 ◽  
pp. 2306-2310
Author(s):  
Qi Han ◽  
Li Zhang
Keyword(s):  
Control System ◽  
Optimal Algorithm ◽  
System Modeling ◽  
Operation Time ◽  
Objective Evaluation ◽  
Multi Objective ◽  
Model And Simulation ◽  
Group Control ◽  
Elevator Group Control ◽  
Time And Energy

Focusing on scheduling of multi-objective optimization in the elevator group control system(EGCS), this article gives a different strategy for dispatching elevator based on improvement of service quality and low energy consumption. Multi-objective evaluation function is modeled base on three factors for average waiting time, average operation time and energy consumption.By making use of particle swarm optimization algorithm to finish the model and simulation of EGCS. Virtual simulation platform should be built by using C++builder6.0.Simulation result indicates the superiority of optimal algorithm

The Intelligent Scheduling Method of Elevator Group Control Based on Fuzzy Neural Network

2012 ◽  
Vol 155-156 ◽  
pp. 653-657
Author(s):  
Yu Lin Dong ◽  
Xiao Ming Wang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Scheduling Algorithm ◽  
Mathematic Model ◽  
Group Control ◽  
Fuzzy Neural ◽  
And Performance ◽  
Elevator Group Control

Elevator group control system (EGCS) is a complex optimization system, which has the characteristics of multi-objective, uncertain, stochastic random decision-making and nonlinear. It is hard to describe the elevator group control system in exact mathematic model and to increase the capability of the system with traditional control method. In this paper, we aim at the characters of elevator group control system and intelligent control, introduce the system's control fashion and performance evaluate guidelines and propose an elevator group control scheduling algorithm based on fuzzy neural network.

Traffic Regularity Evaluation for Elevator Vertical Traffic System

2011 ◽  
Vol 374-377 ◽  
pp. 2301-2304
Author(s):  
Zhen Shan Yang
Keyword(s):  
Control System ◽  
Quantitative Method ◽  
Arrival Rate ◽  
Group Scheduling ◽  
Traffic System ◽  
Group Control ◽  
Scheduling Strategies ◽  
Simulation Results ◽  
Elevator Group Control ◽  
Design Scheduling

To evaluate the regularity strength of elevator traffic (RSET) is the prerequisites to efficiently design scheduling strategies of elevator group control system (EGCS). In view of the characteristics of the uncertainty of elevator traffic, a quantitative method to evaluate RSET is proposed by estimating the confidence interval of 5min passenger arrival rate on observed data, which provides important support for forecasting elevator traffic and adjusting elevator group scheduling strategies. Simulation results of an applied example show the validity of the proposed method.

Twin Elevator Group Optimization Dispatching Based on Genetic Algorithm

2013 ◽  
Vol 415 ◽  
pp. 95-100
Author(s):  
Bao Ding ◽  
Qing Chao Li ◽  
Jin Zhang ◽  
Xiao Feng Liu
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Waiting Time ◽  
Theoretical Basis ◽  
Engineering Application ◽  
Time Algorithm ◽  
Structure Characteristics ◽  
Group Control ◽  
Objective Control ◽  
Elevator Group Control

For the characteristics of a new elevator twin elevator with multiple objectives and uncertainty of group control system ,this work proposed a method of twin elevator group optimization dispatching based on genetic algorithm (GA). On the basis of the analysis of structure characteristics of twin elevator, by means of putting twin elevator running rules into the multi-objective control strategy, the method constructed objective function for twin elevator group; the method utilized GA for the simulation of twin elevator group optimization dispatching, and compared it with the minimum waiting time algorithm. Research results show that the method is able to adapt to the running characteristics of twin elevator, and different traffic flow pattern. Compared with the ones of the minimum waiting time algorithm, average waiting time, long waiting time incidence and the numbers of elevator stops of genetic algorithm are all significantly reduced. Consequently, this method has a strong ability to adapt, and provides a theoretical basis for engineering application of twin elevator group control system.

Sign in / Sign up

Export Citation Format

Share Document