Abstract:
A system for controlling elevator cars in a building having a plurality of floors includes a group controller for controlling operation of the elevator cars. The group controller predicts lobby single source traffic for determined periods. When the predicted traffic is below certain limit, cars are assigned to a lobby hall call on demand after hall call registration. When the predicted traffic is above certain limit, cars are assigned to the lobby hall call at intervals. Accordingly, car assignment is scheduled at those intervals. The schedule interval is varied based on predicted traffic and predicted round trip time of the cars. The cars are assigned to hall calls if they arrive within a schedule window. The schedule window comprises a lower and an upper tolerance that are selected around a scheduled time.
Abstract:
A system for group managing plural elevator cars according to a group management algorithm including plural parameters includes a seeking apparatus for seeking the optimum parameter set, the optimum set being taken from combinations of parameter values given to the group management algorithm. Some new sets are produced by crossover or mutation in the operation of the system. Excellent sets are accumulated in a memory using additional registrations in which excellent sets are additionally stored in the memory and deletions in which impaired sets are deleted from the memory. The optimum set is selected from the accumulated sets, so that the system can efficiently seek the optimum set.
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.
Abstract:
A system including a group controller for controlling the dispatching of elevator cars in a building. The group controller operates by using control parameters stored in its memory. The system records car loads of cars leaving the lobby and the time intervals between their departures and uses fuzzy logic to categorize the car loads and intervals into fuzzy sets. The system determines the lobby traffic and traffic rate using fuzzy relations among car loads, departure intervals, lobby traffic and traffic rate and the fuzzy logic rules. The group controller collects traffic data during operation. The system runs simulations off-line, after single source traffic periods, using the specified control parameter values. The system collects and analyzes performance data to identify significant deviations from acceptable performances. New sets of control parameters are selected using appropriate specified rules. The process of simulation and learning new values of control parameters are repeated until acceptable performance is achieved. The selected parameters are used in system operation. The group controller repeats this process of simulation and learning the parameters periodically.
Abstract:
Each car in a group of elevator cars in a building is determined to be available or not depending on whether it is assigned in the group, whether it is the only delayed car, whether it is fully loaded without intervening car calls which comprise all the car calls, whether it has intervening hall calls, and whether other cars in the group are fully loaded with or without some chance of offloading passengers before reaching a call to be assigned. Among available cars, assignment is made based on each car's membership in fuzzy sets relating to low, medium or high delay in that car responding to the call and each car's membership in fuzzy sets indicative of the extent to which assignment of that car will have no adverse effect or a very high adverse effect on the response to already-assigned hall calls. The call is assigned to the car with the highest summation of weighted memberships in the fuzzy sets.
Abstract:
An elevator control apparatus determines an estimated car delay when the elevator car stops at or passes an elevator hall and controls an operation of the car using the obtained estimated car delay. The elevator control apparatus includes an input data conversion unit for converting traffic data, including position of the car, direction of movement, and car calls and hall calls, such that it can be used as input data of a neural net. An estimated car delay operation unit includes an input layer for taking in the input data, an output layer for outputting the estimated car delay, and an intermediate layer provided between said input and output layers in which a weighting factor is set. An output data conversion unit converts the estimated car delay output from the output layer such that it can be used for a predetermined control operation. The estimated car delay operation unit constituting a neural net.
Abstract:
A traffic volume estimating apparatus 1A estimates the traffic volumes of traffic apparatus, and a traffic flow presuming apparatus 1B presumes the traffic flows generating the estimated traffic volumes. A presumption function constructing apparatus 1C corrects the presumption functions of the traffic flow presuming apparatus 1B on actually measured traffic volumes, traffic flow presumption results and control results. A control result detecting apparatus 1G detects the control results and the drive results of the traffic apparatus. Further, a control parameter setting apparatus 1D sets control parameters on traffic flow presumption results, and corrects the control parameters according to the control results and the drive results.
Abstract:
Fuzzy sets indicative of likelihood of additional weight elevator passengers may have in a given country compared with a standard international low passenger weight, indicative of packages which may be carried up at certain times of day or carried down at certain times of day by passengers in the elevator, and indicative of the weight of additional clothing which may be worn due to different seasons in temperate climates are all added to a basic single passenger fuzzy set so as to more accurately reflect the likely weight of a single passenger. From this are derived fuzzy sets for any number of passengers which may possibly occupy an elevator, which in turn are utilized to provide a passenger fuzzy set indicative of a given weight of the elevator having been caused by various numbers of passengers. Processing details are also disclosed.
Abstract:
The traffic mode of an elevator system is set according to the number and frequency of passengers departing and arriving at a building lobby. The traffic mode is expressed as a fuzzy logic set having a term indicative of up peak mode, a term indicative of down peak mode, and a term indicative of off peak mode. The degrees of membership of each term are indicative of the degrees to which the elevator system exhibits characteristics of the respective modes.
Abstract:
An image of an elevator hall or an inside of elevator car is acquired by photographing apparatus, and the number of waiting passenger is detected by comparing the above-mentioned image with a background image when no passenger is present at the elevator hall. Second image processing apparatus with high precision is prepared by the same image information as that of first image processing apparatus, teacher information derived therefrom is compared with an output from the first image processing apparatus. If the teacher information is not coincident with the output from the first image processing means, parameters required for performing the image process by the first image processing appartus, for instance, constants, threshold values and weight coefficients employed in an image processing algorithm are adjusted.