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基于模糊神经网络的电梯群控系统交通模式识别和多目标优化群控算法研究
Research on Fuzzy Neural Network Based Recognition of Traffic Patterns of Elevator Group Control System and Multi-target Dispatching Algorithm
【作者】 鲍海;
【作者基本信息】 同济大学 , 系统工程, 2007, 硕士
【摘要】 电梯是高层建筑中不可缺少的垂直交通运输工具,随着高层智能建筑的大量涌现,人们对电梯系统的性能提出了越来越高的要求。电梯群控系统是在建筑物内控制三部或三部以上电梯并实现优化调度从而有效的运送乘客改善服务质量的控制系统。本文以电梯群控系统作为研究对象,在对电梯控制技术进行深入分析的基础上,以提高电梯群控系统的运行效率为出发点,以减少候梯时间、减少乘梯时间、节约能耗为目的,对电梯群控系统的派梯策略进行了深入的研究,提出了一种基于交通模式识别控制的多目标优化调度方法。本文首先分析了电梯群控系统的特性、控制方式、性能评价指标及交通流情况。在交通模式识别方面,采用基于联结机制的模糊神经网络对交通流进行辨识,该方法对复杂的交通流具有很好的识别能力,对电梯群控器根据不同的交通状况采用相应的派梯策略可以起到很好的指导作用。为满足在多种交通交通模式下都能适应,本文提出以减少候梯时间、减少乘梯时间、节约能源消耗为控制目标的评价函数,能够根据当前交通模式调节各控制目标权重的多目标规划群控算法。为了测试群控算法的性能,开发了一套电梯群控系统仿真软件。将群控算法编写成程序,即可在仿真软件中进行测试。仿真结果表明,本文提出的算法是有效的。
【Abstract】 The elevator is an indispensable vertical traffic means of transportation in the skysraper, with the emerging in a large amount of the high-story intelligent building, passengers have put forward higher and higher demand to the systematic function of the elevator. Elevator Group Control System(EGCS) is a control system that manages three or more elevators in a building in order to optimize elevator assignment to transport passengers efficiently and improve quality of service.The thesis regards the EGCS as the research object. On the basis of analyzing in depth t o the control technology of the elevator, deep research has been carried on to the group control intelligence system of the elevators regarding improving the systematic intelligent level of EGCS, reducing waiting time, improving the service quality and meeting optimize the needs of modem work as the goal. A kind of new multi-objective intelligent dispatching method has been putting forward by setting up an EGCS controlled on the basis of the traffic pattern-recognition.The thesis analyses the systematic characteristic, control method, performance evaluation index and traffic flow situation of EGCS at first. In traffic pattern-recognition, fuzzy neural network is adopted to distinguish the traffic pattern, this method has very good recognition capability to the complicated traffic flow and can play very good guidance function to adopt the corresponding group control policy to EGCS according to different traffic.In order to be adaptive to different traffic patterns, a multi-objective control method that can adjust the weight of every objective according to the changing traffic patterns is presented in this paper. An evaluation function is established to realize the control objects for reducing average waiting time, riding time and run times of elevators.In order to test the performance of group control algorithms, a set of software of virtual environment of elevator group control system is developed. Make programs of the algorithm and then it can be tested in the simulation environment. The simulation results prove that the multi-objective control method is efficient.
【Key words】 Elevator Group Control System; Traffic Pattern recognition; Multi-objective control; Fuzzy Neural networks;
- 【网络出版投稿人】 同济大学 【网络出版年期】2009年 06期
- 【分类号】TU857
- 【被引频次】15
- 【下载频次】909