Elevator group supervisory control system

• US 5,767,461 A
• Filed: 12/22/1995
• Issued: 06/16/1998
• Est. Priority Date: 02/16/1995
• Status: Expired due to Term

• Current Assignee: Fujitec Company Limited
• Original Assignee: Fujitec Company Limited
• Inventors: Ohta, Naoki, Markon, Sandor, Nakagawa, Masami, Tanabe, Tomoaki, Nagashima, Ichiro, Midoritani, Takeshi, Sasaki, Kenji
• Primary Examiner(s): NAPPI, ROBERT E
• Application Number:
  US08/576,937
• Time in Patent Office: 907 Days
• Field of Search: 187/380, 187/382, 187/387, 187/247
• US Class Current: 187/382
• CPC Class Codes: B66B 1/2458 For elevator systems with multiple shafts and a single car per shaft
• CPC Class Codes: B66B 2201/102 Up or down call input
• CPC Class Codes: B66B 2201/211 Waiting time, i.e. response time
• CPC Class Codes: B66B 2201/214 Total time, i.e. arrival time
• CPC Class Codes: B66B 2201/215 Transportation capacity
• CPC Class Codes: B66B 2201/216 Energy consumption
• CPC Class Codes: B66B 2201/222 Taking into account the number of passengers present in the elevator car to be allocated
• CPC Class Codes: B66B 2201/233 Periodic re-allocation of call inputs
• CPC Class Codes: B66B 2201/402 by historical, statistical or predicted traffic data, e.g. by learning

Abstract

An elevator group supervisory control system for selecting the most suitable car among a plurality of elevators, when a hall call is made, to assign to the hall call, comprising: temporary assigning means for temporarily assigning the car by a conventional method such as a fuzzy group supervisory control based on group data representing states of the elevator system at the moment when a new hall call is made; and a neural net for receiving numerical values converted from group data including the result of judgment of the temporary assigning means and outputting an assignment fitness of each elevator. It decides the most suitable elevator from the output pattern of the neural net to assign to the hall call.

Claims

1. An elevator group supervisory control system for providing service of a plurality of elevators to a plurality of floors by selecting the most suitable car among them, when a hall call is made, to assign to the hall call, comprising:

temporary assigning means for performing a first step assignment operation producing first step data indicating an optimal elevator based on group data indicating various states of said elevators when the hall call is made;

a neural net for receiving input patterns in which the first step data of said first step assignment of said temporary assigning means is converted into numerical values together with other group data and outputting an assignment fitness for each of said elevators as an output pattern which indicates a selected one of said elevators to be assigned to said hall call; and

assigning means for assigning the selected one of the elevators at a second step based on the output pattern of said neural net.

7. The elevator group supervisory control system according to claim 1, wherein the first-step assignments made by said temporary assigning means, is performed by an artificial intelligence-based group control.

8. The elevator group supervisory control system according to claim 7, wherein said artificial intelligence-based group control is a fuzzy group control.

2. An elevator group supervisory control system for providing service of a plurality of elevators to a plurality of floors by selecting the most suitable car among them, when a hall call is made, to assign to the hall call, comprising:

temporary assigning means for temporarily assigning the car based on group data indicating various states of said elevators when the hall call is made;

a neural net for receiving input patterns in which the result of assignment of said temporary assigning means is converted into numerical values together with other group data and outputting an assignment fitness as an output pattern;

assigning means for deciding the elevator to be assigned from the output pattern of said neural net;

learning means for implementing an initial learning of said neural net; and

switching means for switching between the assignment by means of said temporary assigning means during the initial learning and the assignment by means of said neural net after completion of the initial learning.

3. The elevator group supervisory control system according to claim 2, wherein the assignment made by said temporary assigning means is an assignment made by means of a fuzzy group supervisory control.

4. The elevator group supervisory control system according to claim 2, wherein the initial learning of said neural net consists of a preliminary learning in which the waiting time of a hall call is adopted as a teacher signal and an objective learning in which the assigned elevator is adopted as a teacher signal.

5. The elevator group supervisory control system according to claim 4, wherein learning samples, in which only a waiting time of the assigned elevator is adopted as the teacher signal, are used in the preliminary learning and a connection weight, connected to the neuron to which the teacher signal is supplied, is modified in the output layer of the neural net to reflect the value after the modification to connection weights connected to other neurons at symmetrical positions.

6. The elevator group supervisory control system according to claim 4, wherein said neural net is constructed so that the input layer and a middle layer are common and an output layer which corresponds to the assigned elevator and an output layer which corresponds to the waiting time of the hall call are separately provided to implement the preliminary learning and the objective learning simultaneously.