Single Elevator PLC Control To The Research Of Elevator Group Control System

With the continuous progress and development of society, there are more andmore high-rise buildings. The number of elevators in high-rise buildings also increasedby a single to multiple.How to make an elevator to provide high quality service, hasalways been the hot spot of the many control domain experts to research. From thetraditional single elevator control to more than one elevator group control, people areconstantly on the study of the optimal control method. Now elevator common problemis to modify traditional relay control of elevator and to research elevator group controlscheduling algorithm. But we also see more complexity and hardships of the elevatorcontrol problem, with great challenge. Elevator optimal control brought economic andenvironmental benefits are huge.Programmable logical controller from the date of birth, its excellent reliability andstability, making use of the rapid expansion in the elevator industry. It is thedevelopment of the relay control for logical contactless control the epoch-makingproduct. Now the elevator control and transformation process commonly used PLC.The elevator industry in our country introduces the PLC technology in the80s. Manycontrol systems developed for its excellent performance has been widely praised. Withthe combination of computer monitoring system, people can run the monitoring of theprocess of moving elevator.Inside a building elevator to realize the optimal control of the premise is toanalyze the traffic volume of the building. The analysis of traffic flow use clusteringclassification method. In the first step, due to its immune stimulation mechanism,immune suppression mechanism and Immune memorization mechanism, the newlydeveloped artificial immune system is employed to extract the feature data from theoriginal elevator traffic data and then the reduced traffic data is obtained, which is alsocalled the immune memory dataset or feature dataset. In the second step, thehierarchical clustering and support vector clustering are employed respectively in clustering analysis of the elevator flow feature dataset. We evaluate the performance ofparameters. Experiments show that this chapter puts forward the analysis method hashigh theoretical value and practical value.Elevator group control scheduling algorithm is the core of elevator group controlsystem, the research on which has important guiding significance and practicalsignificance to improve the Service efficiency of elevator. Consider the elevator groupcontrol system control objectives nonlinear and multi-objective nature, we controlbased on the basis of previous ideas and experiences, draw fuzzy multi-segmentmulti-objective scheduling rules. By objective function after the completion of thegeneral description, to take appropriate control strategies for different traffic verifypassenger model, analyzed by simulation experiments on the reliability and validity ofthe algorithm.