Research Of Scheduling Algorithm In The Elevator Group Control System

Elevator, as vertical transporting facility is more and more widely used with the emergence of intelligent buildings. The quality of elevator services needs to be improved to satisfy the passengers, requirements. Single elevator is insufficient for the inner building transportation. Multi-elevator service could shorten the waiting time and reduce energy consuming. As a consequence, the elevator group control system is introduced. The elevator group control system improves the service efficiency and quality by an optimized control policy, which harmonizes multi-elevator operation.The elevator group control system is through monitoring and analyzing the operation state of elevator group in real time, then optimize regulation and assign rationally for every elevator according to different actual conditions, and then realize the goal of the improving of the elevator system's service quality and efficiency.This thesis analyzes the requirement of the passenger on the elevator group control system and the characteristic of the system, summarizes the existing control modes, sets up the model of the transportation pattern by fuzzy neural network which is used to predict the traffic flow according to the statistical information in certain time slot, and analyzes the group controlling arithmetic, which sets up the assessment function based on multi-objective planning and emphasizes different requests under different traffic mode through weights. The elevator can be assigned through transferring different group controlling arithmetic according to the traffic mode predicted. Finally, this thesis has verified the validity of the arithmetic through simulating the model.This thesis designs the management arithmetic under different traffic mode according to the complicated characteristic of the elevator group control system. The system performance can be greatly improved through using the most suitable arithmetic in different traffic mode.