电梯群联动优化算法的研究

发布时间：2018-03-13 04:12

本文选题：电梯群联动控制系统　切入点：客流模式　出处：《南昌航空大学》2017年硕士论文　论文类型：学位论文

【摘要】：电梯群联动控制系统是一种用于高层建筑物垂直交通的智能控制系统,随着高层建筑数量的增加和对各种资源利用率的提升,人们对电梯群联动系统的要求也日益增高。除了提高电梯群的硬件配置之外,对电梯群的调度控制算法进行优化也是一个至关重要的方面,因此本文对如何优化电梯群的控制算法进行了分析研究。首先,本文研究了电梯群联动控制系统的发展过程和国内外发展现状,通过对发展过程的了解总结了几种常见的智能控制算法,并分析了各种算法的优点和不足之处。基于电梯群的多目标、多元化特点,建立电梯群联动控制系统的多种性能评价指标。然后针对办公大楼的客流量进行统计分析,找出不同客流模式下电梯群的调度问题,在理论上提出了几种电梯调度方法来应对不同客流交通模式。其次,建立电梯群联动系统的数学模型,确定电梯群优化控制目标,在Matlab仿真环境下对不同客流模式进行了设计与仿真,并且用最短候梯时间算法、改进的自适应粒子群算法以及混合粒子群算法对电梯群联动控制系统进行了算法设计和仿真对比。仿真结果表明,两种改进的粒子群算法对平均候梯时间和平均乘梯时间具有更好的控制效果,验证了算法的有效性,实现了在不同交通模式下对电梯群联动系统的优化调度控制。最后,在Delphi 6.0编程环境下,设计两种不同的电梯群联动仿真系统:传统电梯群仿真和目的层预约型电梯群仿真。在传统仿真系统中调用了最短候梯时间算法进行轿厢调度的优化,在目的层预约型仿真系统中调用了文中提到的三种不同优化算法来优化轿厢的调度问题。通过对调用不同的算法得出的乘客平均候梯时间、平均乘梯时间和轿厢累计运行楼层三种数据进行分析,结果表明三种优化算法都在对群控调度问题上有较好的控制效果,进一步验证了算法的实用性。
[Abstract]:Elevator group linkage control system is an intelligent control system for vertical traffic of high-rise buildings. With the increase of the number of high-rise buildings and the improvement of the utilization of various resources. In addition to improving the hardware configuration of the elevator group, it is also a crucial aspect to optimize the dispatching and control algorithm of the elevator group. Therefore, this paper analyzes and studies how to optimize the control algorithm of elevator group. Firstly, this paper studies the development process of elevator group linkage control system and the development status at home and abroad. Based on the understanding of the development process, this paper summarizes several common intelligent control algorithms, and analyzes the advantages and disadvantages of these algorithms. A variety of performance evaluation indexes of elevator group linkage control system are established. Then statistical analysis is carried out on the passenger flow of office building to find out the dispatching problem of elevator group under different passenger flow modes. In theory, several elevator dispatching methods are put forward to deal with different passenger traffic modes. Secondly, the mathematical model of elevator group linkage system is established, and the optimal control goal of elevator group is determined. Different passenger flow modes are designed and simulated in Matlab simulation environment, and the shortest waiting time algorithm is used. The improved adaptive particle swarm optimization algorithm and hybrid particle swarm optimization algorithm are used to design and simulate the elevator swarm linkage control system. The simulation results show that, The two improved particle swarm optimization algorithms have better control effect on the average waiting time and the average riding time. The validity of the algorithm is verified, and the optimal dispatching control of the elevator group linkage system under different traffic modes is realized. Finally, In the Delphi 6.0 programming environment, two different elevator group linkage simulation systems are designed: the traditional elevator group simulation and the target layer reservation elevator group simulation. In the traditional simulation system, the shortest waiting time algorithm is used to optimize the car scheduling. Three different optimization algorithms mentioned in this paper are used to optimize the scheduling problem of the car in the target layer reservation simulation system. The average waiting time of passengers is obtained by calling different algorithms. The results show that the three optimization algorithms have better control effect on the group control scheduling problem and further verify the practicability of the algorithm.
【学位授予单位】：南昌航空大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU857;TP273;TP18

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