Novel RS-FNN control policy in hybrid elevator group control system with destination registration

Abstract

Elevator group control system with destination registration (DR-EGCS) has become hotter in these years. This paper analyzes and obtains the new characteristic attribution in destination registration elevator group control system, firstly builds up a new hybrid elevator group control system with destination registration model is built up based on hybrid system theory and cellular automata. And then aiming at the problem of how to mine the huge complicated, redundant and incomplete original elevator data effectively, one novel elevator group control method combined rough set theory and fuzzy neural network is present. The simulation results show that this proposed hybrid DR-EGCS model is correct and effective. Novel elevator group control method can improve elevator system performance and adapt complicated traffic flow in variable elevator traffic flow conditions. This control method also can be applied to other similar fields.