Studies Of Elevator Group Control System Based On Fuzzy Neural Network

In recent years, elevator services become a must in higher buildings, then, one elevator couldn't satisfy all needs of passengers in most of the cases. In order to cut down waiting time,reduce power consumption, it is better to put many elevators together and monitor them together in reason. This optimization dispatching system to all the elevators is named elevator group control systems (EGCS). As randomness, nonlinearity, and difficulty to setup an exact mathematics mode, using intelligent control methods to elevator group is a necessary. In this paper, Fuzzy Neural Network was studied and fuzzy reasoning was realized by use of neural networks structure. BP algorithm is used to optimize local parameter.Fuzzy neural network elevator group control system (FEGCS) has been discussed. This article proposes a new elevator group control system from the view of passengers which addresses riding time as well as waiting. It considers both the mental need and physical requirement of passengers. We take several evaluation criteria of the elevator function into account and make the rules of logic.At last, simulation was made under virtual environment. Compared with conventional EGCS, elevator group control using fuzzy neural network can be used not only to variety traffic, but can also meet all needs of single traffic mode.