基于PLC电梯群控系统的设计与研究

发布时间：2017-12-27 00:00

本文关键词：基于PLC电梯群控系统的设计与研究　出处：《太原理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着科学技术的进步和城市化的推进,高层与智能建筑作为现代城市的标志不断涌现。作为垂直运输工具,电梯主要用来完成人或物的输送,这在建筑物内的作用不言而喻。因此对于电梯控制的研究非常有意义。伴随着生活质量提高,人们对电梯性能的要求也变得越高,比如操作简洁、乘梯舒适、节约能源等。电梯控制系统也随之经历了快速发展,从原来的单部电梯控制、相对复杂的并联运行控制,再到多部电梯智能化联合控制。电梯控制技术的发展有效的提高了电梯运行系统的稳定性,极大的改善了用户乘梯体验。本文首先介绍了电梯控制技术的发展历程及研究现状,分析了电梯控制系统的基本原理和结构,运用S7-1200 PLC和TIA Portal全自动集成开发环境搭建了电梯控制系统的运行环境。通过PLC对电梯控制程序进行模块化编程,并对重要模块详细分析,从而实现单部电梯的程序设计。其次研究了两部电梯并联控制算法,根据最快响应原则,将其程序实现。其间通过TIA Portal WINCC监控电梯运行状态:包括轿厢位置、内外呼登记、故障报警、优先调度等。并通过实时观测,根据电梯运行状态信号模拟调试,使电梯控制系统安全、高效的运行。然后,在单部电梯控制和两部电梯并联调度设计基础上,着重对群控系统展开研究。简要介绍了电梯运行中的不同交通模式以及群控系统的常用控制方式。基于群控系统的不确定性、非线性、扰动性以及多目标性等复杂特性,对控制系统做了多目标规划处理。由于电梯群控系统难于建模,运用模糊逻辑思想构造了影响控制目标主要因素的隶属函数,并在详细分析BP神经网络结构及算法原理的基础上,建立了一个以隶属度为输入、综合评价指标为输出的BP网络模型。通过MATLAB对神经网络进行了学习训练,并经过测试最终得到优化的各项权系数。最后,在PLC构建的实践仿真平台给予程序实现,结合监控画面,对群控调度算法进行仿真测试。通过分析运行数据,验证了群控调度算法的有效性和在实际PLC中应用的可行性。
[Abstract]:With the advancement of science and technology and the advancement of urbanization, high level and intelligent buildings are emerging as the symbols of modern cities. As a vertical transport tool, the elevator is mainly used to carry out the transportation of people or things, which is self-evident in the function of the building. Therefore, the research on elevator control is of great significance. With the improvement of the quality of life, the higher the requirements for the elevator performance, such as simple operation, ride comfort, energy saving and so on. The elevator control system has also experienced rapid development, from the original single elevator control, relatively complex parallel operation control, and multiple elevator intelligent joint control. The development of elevator control technology effectively improves the stability of the elevator operation system, and greatly improves the user's ladder experience. This paper first introduces the development process and research status of elevator control technology, analyzes the basic principle and structure of elevator control system, and builds operation environment of elevator control system by using S7-1200 PLC and TIA Portal automatic integrated development environment. The elevator control program is programmed by PLC, and the important module is analyzed in detail so as to realize the program design of the single elevator. Secondly, two parallel elevator control algorithms are studied, and the program is implemented according to the fastest response principle. In the meantime, the TIA Portal WINCC is used to monitor the operation of the elevator, including the car position, the inside and outside call registration, the fault alarm and the priority scheduling, etc. And through real-time observation, according to the elevator running state signal simulation and debugging, make the elevator control system safe and efficient operation. Then, on the basis of single elevator control and two elevator parallel dispatching design, the research of group control system is emphasized. This paper briefly introduces the different traffic modes in the elevator operation and the common control methods of the group control system. Based on the complex characteristics of uncertainty, nonlinearity, disturbance and multi-objective of the group control system, multi-objective programming is done to the control system. The elevator group control system is difficult to model, using the membership function of fuzzy logic to construct the main factors affecting the control objectives, and based on the detailed analysis of the BP neural network structure and algorithm principle, the establishment of a membership for the comprehensive evaluation index for the input and output of the model of BP network. The learning and training of the neural network is carried out through MATLAB, and the optimized coefficients are finally obtained through the test. Finally, the practical simulation platform constructed by PLC is implemented, and the group control scheduling algorithm is simulated and tested in combination with the monitoring screen. Through the analysis of the running data, the effectiveness of the group control scheduling algorithm and the feasibility of application in the actual PLC are verified.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP273;TU976.3

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