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Advanced AI Supervisory
Control
Mitsubishi Electric's AI Supervisory Control is the
key factor in creating an ideal elevator system with optimum user service. Two
basic systems are available, and between them they offer a wide range of special
functions to suit the needs of any type of building.
AI-22
System
Mitsubishis AI Supervisory Control is the
key factor in creating an ideal elevator system with optimum user service. Two
basic systems are available, and between them they offer a wide range of special
functions to suit the needs of any type of building.
AI-2200
System
This system is designed for larger buildings
with three to eight cars in the elevator group. It suits buildings with dynamic
traffic conditions throughout the day and peak carrying times.
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:
Standard,
: Option, -: Not Applicable |
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Configuration
of AI-2200
System
Expert System and Fuzzy Logic
The brain of the AI Supervisory Control employs an intelligent Expert System
that uses the practical knowledge and experience of elevator group control
experts. This information is stored in the systems memory as a "Knowledge
Database". Drawing from this database, various traffic conditions are
monitored and analyzed applying IF-THEN decision rules to maximize the effectiveness
of each elevator operation. Mitsubishi Electric applies fuzzy logic
that enables the elevator control system to make decisions using
fragmentary and fuzzy logic intelligence concepts. The assessment results
are applied to determine the car assignments in order to improve overall
service. |
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Psychological
Waiting Time Evaluation
This evaluation function is Mitsubishi Electric technology that originates
from the psychological thought patterns of a passenger waiting for an elevator:
the irritation of a passenger waiting for elevator arrival is proportional
to the square of the actual waiting time. Elevator assignments to hall calls
are performed on the basis of evaluation results. In addition to forecasted
waiting time, factors such as probability of being bypassed for a hall call,
probable time required for traveling after car assignment, current car load
and others are applied in the evaluation function owing to its coefficient
diversity. Car assignments to hall calls are made as a sum of all factors.
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Strategic
Overall Assignment
Combining all building traffic conditions, the system forecasts where
future service will be needed and assigns cars accordingly. This greatly
reduces the average overall waiting time and provides optimum service to
passengers throughout the building.
Once all car and hall calls are serviced, the system forecasts where
the next calls for service will arise and assigns the cars so
that the waiting time for future passengers is also reduced. (Strategic
Overall Spotting) |
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Immediate
Prediction Indication*1
Once a passenger has registered a hall call, the ideal car to respond is
selected, the hall lantern lights, and a chime sounds once to indicate
which door will open. As the car approaches, the lantern begins to flash
and the chime sounds twice. This system provides a highly reliable prediction
of car arrival and reduces passenger irritation. |
*1: Available only for AI-2200. |
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Distinction
of Traffic Flow with Neural Networks*1
Elevator operation in optimum service patterns is essential for efficient transfer of passengers in a building. To ensure the efficiency, service patterns shall be adjusted according to the passenger flows inside the building, which fluctuate constantly depending on the time zones such as morning up peak, lunchtime and evening down peak. Mitsubishi's AI-2200 System adopts the Neural Networks technology as the core tool to precisely recognize the current traffic flow in real time, and to select the optimum service pattern in a timely manner. In this technology, ideal "sets of rules" are selected for each traffic pattern and for each day of the week, using the passenger flow data calculated by the past records of the car load, as well as the frequency of car and hall calls on each floor. At the same time, traffic flow in the next several minutes is predicted based on both past and current operation data, then the selected rule sets are simulated under the predicted flow in order to determine the optimum service pattern. By accumulating data on actual elevator operations, the accuracy in predicting traffic flows and in selecting optimum service patterns is enhanced, and optimum elevator service can be delivered.
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*1: Available only for AI-2200. |
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Car
Allocation Tuning*1
The AI-2200 system applies a refined algorithm
to improve the average waiting times at each floor in the building,
controlling the number of elevator cars allocated or parked on the crowded
floors during peak periods in incoming, outgoing and lunchtime traffic.
The algorithm covers the situation of elevator services, the conditions
of elevator operations, etc., as well as the degree of traffic density or
flows. The tuning process is described as follows:
Step 1: The initial number is set as crowds gather.
Step 2: The data of each elevator operation is collected.
Step 3: And then, the initial allocation number is tuned to be increased
or decreased according to the fuzzy rules. |
*1: Available only for AI-2200. |
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Destination
Oriented Prediction System*1
Press the destination floor, and the service elevator is indicated immediately
When a passenger presses a destination floor button on the newly developed
hall operating panel, the
code letter for the service elevator immediately appears next to the destination
floor button. The passenger knows at a glance which elevator to board.
Because the Destination Oriented Prediction System analyzes passengers'
destinations to reduce passenger travel times and minimize
congestion, the system greatly improves traffic efficiency, particularly
in peak times. In addition, since the passengers destination floor is registered
automatically, theres no need to press the floor button again after boarding
the elevator. |
*1: Available only for AI-2200. |
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Motor
Drive Mix
By increasing elevator acceleration between floors, waiting time during
congested periods is reduced.
The elevators acceleration and deceleration rates are adjusted according
to car load and traffic conditions to maximize driving system efficiency.
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AI-2200
Performance
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AI-2100N*2:
Previous Mitsubishi group control system. |
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