Susumu Kubo

Elevator group control system tuned by a fuzzy neural network applied method

We have developed a high-performance elevator group control system with a performance tuning function, which employs a fuzzy neural network as a performance forecasting model of the elevator system. The fuzzy neural network, which is a structured neural network based on a fuzzy reasoning framework, stores the correlation between control-parameters and the response of the elevator group as a fuzzy rule set. It performs a fuzzy rule-based reasoning to forecast the system performance of the elevator group. The performance tuning function utilizes the forecasting model in order to search the optimal control parameters which give the best system performance in the present traffic situation. The fuzzy neural network applied system can automatically adapt itself to various traffic situations. This paper gives the overview of the elevator group control system with the fuzzy neural network and shows the validity of the methodology by some simulation results.<<ETX>>

Elevator group control system with a fuzzy neural network model

We have developed a high-performance elevator group control system EJ-1000FN with a performance tuning function, which employs a fuzzy neural network as a performance forecasting model of the elevator system. The performance tuning function utilizes the forecasting model in order to search the optimal control parameters which give the best system performance in the present traffic situation.<<ETX>>