基于模糊神经网络算法的电梯群控系统研究

发布时间：2018-06-04 09:54

本文选题：电梯群控 + 模糊神经网络　；参考：《福州大学》2014年硕士论文

【摘要】：近年来,电梯已是高层建筑的必需品,然而,通常情况下一台电梯满足不了乘客的需要。为了降低等候时间,减少能耗,通常把多台电梯安装在一块,实行集中监控,我们把这种集中监控系统称作电梯群控系统(EGCS)。鉴于电梯群控是一个随机复杂的非线性系统,因此有必要对电梯群采用人工智能控制的方法建立一个精确的数学模式。本文主要研究模糊神经网络,以及实现模糊推理在神经网络结构中的运用,采用BP神经网络优化部分参数。本文提出了基于模糊神经网络的电梯群控系统(FEGCS),从候梯乘客和乘梯乘客的角度出发,它不仅考虑了乘客的心理需要和生理请求,同时综合考虑了电梯运行的评价函数和相应的模糊准则。最后,对模糊神经网络的电梯群控系统与采用传统的电梯群控方法进行仿真比较,结果表明模糊神经网络群控系统对于各种电梯交通模式或某一特定模式下都能得到较好的控制效果。
[Abstract]:In recent years, elevators have been a necessity for high-rise buildings. However, usually, an elevator can not meet the needs of passengers. In order to reduce the waiting time and reduce the energy consumption, many elevators are usually installed together and centralized monitoring is carried out. We call this centralized monitoring system as the elevator group control system (EGCSA). In view of the fact that elevator group control is a random and complex nonlinear system, it is necessary to establish an accurate mathematical model for elevator group by using artificial intelligence control method. In this paper, the fuzzy neural network and the application of fuzzy reasoning in neural network structure are studied. BP neural network is used to optimize some parameters. In this paper, an elevator group control system based on fuzzy neural network (FNN) is proposed. It not only takes into account the psychological needs and physiological requests of passengers, but also takes into account their psychological needs and physiological requests. At the same time, the evaluation function of elevator operation and the corresponding fuzzy criterion are considered synthetically. Finally, the elevator group control system based on fuzzy neural network is simulated and compared with the traditional elevator group control method. The results show that the fuzzy neural network group control system can obtain better control effect for various elevator traffic modes or a particular mode.
【学位授予单位】：福州大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TU857;TP183

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