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The Scheduling of Multi-objective Elevator Group Control Algorithm Based on PSO

Author: LiSuFang
Tutor: LiuYueMin
School: Henan University of Science and Technology
Course: Detection Technology and Automation
Keywords: Elevator Group Control System Particle swarm optimization algorithm Dynamic Analysis Intelligent Control
CLC: TU857
Type: Master's thesis
Year: 2010
Downloads: 154
Quote: 2
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Abstract


With the continuous development of high-rise buildings and intelligent buildings, the elevator as a vertical transport more widely used, it is the quality of elevator service also made a relatively high demand, single lifts building can not meet the traffic demand , in order to shorten the waiting time and riding time, reduce energy loss, reasonable installation of lifts. For more lifts control, an optimized scheduling system, this multi-lift optimization scheduling system, elevator group control system. It uses an optimized control strategy to manage the multiple lifts coordination operation, in order to improve the operation of the elevator efficiency and service quality. Due to the the control objectives diversity of the elevator group control system, itself has randomness and non-linear, so it is a difficult to solve multi-objective optimization problem. This paper analyzes and studies the system of the elevator group control system characteristics, performance evaluation and building traffic patterns, summarizes the existing elevator group control algorithm. On this basis, the weighted average of the three evaluation index in order to reduce the average waiting time, to reduce the average boarding time and reduce the energy consumption of the system is running as a comprehensive evaluation of the elevator dispatching functions, and the the three weighting coefficient is adjusted according to the different transport modes . Particle swarm optimization algorithm and multi-objective particle swarm optimization algorithm, particle swarm optimization framework, in order to adapt to the degree of function design as the core, the multi-objective particle swarm optimization algorithm is applied to elevator group control. With three control objectives based on particle swarm optimization algorithm to solve different traffic patterns and elevator group control system intelligent scheduling. The Visual Basic6 language preparation of elevator group control system dynamic performance analysis software in the Windows 2000/XP environment, build the structure of elevator group control system development, the development structure for testing elevator group control algorithm simulation elevator is running, the elevator configuration provides a convenient and effective simulation platform. Finally, the development of the structure of the design group control algorithm simulation test, simulation results show that the elevator group control system based on particle swarm optimization in the different modes of transport elevator group scheduling. Average Hou ladder time, take the the staircase time and the system is running average energy consumption than traditional group control algorithms have significantly reduced optimization to improve the system efficiency, increased passenger satisfaction, to achieve the purpose of energy saving system.

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CLC: > Industrial Technology > Building Science > Housing construction equipment > Mechanical and Electrical Equipment > Elevator Engineering
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