Research And Design Of Elevator Group Control System Based On Artificial Immune Algorithm

In modern intelligent buildings, people always equip for a building several elevators because of big flux of passengers and varities of factors uncertian. Elevator Group Control System manages the operation of the elevators by optimizing control strategy in order to enhance running efficiency of elevator and improve service quality. With the development of artificial intelligent control technology, the objective of elevator group control system has not limited to reducing waiting time, some other objectives such as reducing riding time and reducing the power consumption are also taken into consideration. The thesis designs a Elevator Group Control System based on Artificial Immune Algorithm, in order to suit for the feature of peak passenger flow time and solve the problem remaining during this time.Artificial Immune System is a newly emerging method'in Artificial Intelligence. It has data feature extraction function.The thesis does a simulation experiment of feature extraction to two groups the data which simulate the elevator passenger flow using the Artificial Immune Algorithm,whose effect is well. In the deeply research of Artificial Immune Algorithm, however, the thesis found that, there is some insufficiency when the thesis solutes optimization question with Artificial Immune Algorithm based on Clonal Selective Theory. Mainly, the insufficiency is that the thesis couldn't always get a satisfying curve about the aspect of keeping the maxmum affinity. The thesis analyses the problem carefully and find out the reason, then, improves the Artificial Immune Algorithm based on Clonal Selective Theory. Through the simulation, the thesis gets a satisfying effect.On peak passenger flow time, zoning is a effictive method on soluting elevator group scheduling problem.However, the zoning method that we use now is fixed or determined according to the time in advance. They cannot adapt the actual transportation pattern. It also makes some people to have the opposition manner to zoning research. Dynamic zoning has the very big flexibility, it also has the very big superiority on the aspect of increasing the seating capacity, reducing the waiting time and riding time, reducing the energy consumption and so on. Whereas, how to fix the zoning mode quickly is the difficulty of the problem.The thesis found that the Artificial Immune Algorithm may solve it well exactly. The thesis uses the Artificial Immune Algorithm in the elevator dynamic zoning process, and carrys on a simulation experment.At last the thesis confirms its feasibility and validity, then makes the elevator dynamic idea ot be able to realize well.