Research On The Algorithm Of Elevator Group Control Based On Fuzzy Control

With the rapid development of high-rise and intelligentized buildings, the higher requirement of the elevators has been put forward. In order to improve the transport capability and the service quality, elevator control technology has been transferred from control of single elevator to the cooperative control of multiple elevators, that is elevator group control. How to realize elevator group control is becoming increasingly an important subject of concern.Because of the randomness of elevator traffic and many characters of the elevator group control system, such as many targets, the uncertainty, the no linearity, the disarrangement and short of maturity in information, so it is very difficult for us to establish an accurate model of controlled object. The fuzzy control technique has great advantages in resolving these problems. It does not need to establish an accurate model for the problem, but analyze, calculate and ratiocinate based on the related knowledge, and can simplify many complicated problems. So the fuzzy control technique is applied to the Elevator Group Control System (EGCS), which can solve the problems well in the EGCS.Application research status and existing problems of fuzzy control technology in the EGCS are analyzed in this thesis. The feasibility and the necessity of applying fuzzy control technique to the EGCS are analyzed as well. The overall architecture of Fuzzy Elevator Group Control System (FEGCS) and the passenger flow distribution of elevator traffic are analyzed in detail. The traffic components and the traffic intensity in the building are regarded as the input variables of fuzzy reasoning, and the rules base of traffic pattern identification is built. Then nine traffic patterns according to ninteen fuzzy reasoning rules at two'steps are summarized. The fuzzy reasoning using Max-Min method can identify the current traffic pattern.Considering comprehensive evaluation system of traditional EGCS has its own disadvantage, a more reasonable comprehensive evaluation function is built up. The low average waiting time, the low average riding time, the low long-time waiting percent and the low power consumption are the most important four evaluation indexes whose weighted average value is acted as the evaluation function. The weight coefficients are adjusted according to different traffic patterns to realize optimization scheduling control of elevator group by final assignment of elevator calling signals.Fuzzy reasoning process of four evaluation indexes is studied in detail in this thesis. New subordinate functions of input variables are confirmed and the fuzzy reasoning rules base of every evaluation index is built. Meanwhile, the relationship between the credibility of every evaluation index and input variables is simulated by the simution of MATLAB. The experimental datas show that the change of input can better reflected fuzzy reasoning output value of four evaluation indexes, also further verifies the effectiveness of subordinate functions for input variables and the validity of the fuzzy reasoning.Finally, the fuzzy elevator group control dispatching algorithm designed in this thesis is compared with genetic algorithm, minimum waiting time algorithm and the shortest distance algorithm by the simution of MATLAB. Under the same simulation environment, three simulation examples show that when arrivals in a certain period, elevator layers and numbers have changed, this algorithm is superior to other algorithms. It can be easily extended and used for general purpose, verifying that the algorithm in this thesis can realize the optimization control of elevator group. It fully shows great efficiency and feasibility of elevator group control algorithm based on fuzzy control.