Research on elevator group control system based on the fuzzy neural network

Author(s):  
Yu Ai-rong ◽  
Cao Lei ◽  
He Yi-hui ◽  
Yang Fei
2012 ◽  
Vol 155-156 ◽  
pp. 653-657
Author(s):  
Yu Lin Dong ◽  
Xiao Ming Wang

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.


2010 ◽  
Vol 29-32 ◽  
pp. 2726-2732
Author(s):  
Huo You Li ◽  
Jian Jun Li ◽  
Jian Yang Li

This paper has proposed a concept of Group Control Object, taking an example according to experimental data of elevator group control object of a building; we apply fuzzy logic and neural network to recognize the pattern of the group control object. With the aid of the fuzzy neural network, this task designs to identify the different passenger flow, and classify it into the six models such as the up-peak service model, down-peak service, two way traffic model, four way traffic model, the balanced bi-story traffic model and free duty traffic model. Then it constructs five-level fuzzy neural networks to apply the classification to the elevator group control, and perform the best group control strategy for each model.


2011 ◽  
Vol 110-116 ◽  
pp. 4076-4084
Author(s):  
Hai Cun Du

In this paper, we determine the fuzzy control strategy of inverter air conditioner, the fuzzy control model structure, the neural network and fuzzy control technology, structural design of the fuzzy neural network controller as well as the neural network predictor FNNC NNP. Simulation results show that the fuzzy neural network controller can control the accuracy greatly improved the compressor, and the control system has strong adaptability to achieve a truly intelligent; model of the controller design and implementation of technology are mainly from the practical point of view, which is practical and feasible.


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