JPH01236178A - Controller for elevator group - Google Patents

Abstract

PURPOSE:To improve the free use of a user by changing a sensitivity target set in response to the sensitivity of the user into a control target through the use of a variable function obtained from a questionnaire investigation or the like, and replacing control targets mutually related with control methods. CONSTITUTION:A group controller is made up of three large blocks consisting of a sensitivity target setting means 2, a target changing means 3 and a control executing means 4. The sensitivity target setting means 2 sets the sensitivity target values (viz. a sense of value, interest, taste, feeling and likes and dislikes, and so on) and an elevator use environment. The target changing means 3 is equipped with a variable function for every elevator use environment against the predetermined item of a sensitivity target, and a change into the control target of the elevator is made through the use of this variable function. Further, the control executing means 4 decides the operation situation of the elevator or the like on the basis of data from a hall calling control portion 5 and the control portions 6, 7, 8 of respectively numbered machines, and takes out control method and calling assignment method housed at a table and execution is made, and its result is transmitted to the respectively numbered machines.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to an elevator group management control device, and particularly to a control device suitable for realizing control corresponding to the sensibilities of users.

[Conventional technology]

Conventionally, in the elevator group management control device, the elevator
With the aim of improving operating efficiency and improving passenger service,
The hall calls that occur are monitored online, and the service status of all hall calls is taken into account to determine the optimal elevator.
A method has been adopted to reduce the average waiting time by allocating calls to Recently, when selecting an elevator from among a plurality of elevators to which a hall call is to be assigned, a variable parameter is added to the evaluation function for evaluating each elevator, and the variable parameter is added to the evaluation function for evaluating each elevator. Parameter values are changed and the obtained results are used to learn parameter values that satisfy preset target values, and call assignment control is executed using the parameters according to the operating status of the elevator. This method has been proposed in Japanese Patent Laid-Open No. 58-52162, Japanese Patent Laid-Open No. 58-63668, etc.

[Problem to be solved by the invention]

The above conventional technology reduces the average waiting time by 1.
Although this could alleviate the dissatisfaction of passengers, it still had some problems.

Specifically, long waiting times occur on certain floors at the same time every time, calls are assigned to elevators far away even though there is a waiting elevator nearby, and the number of wagons etc. This elevator was assigned to a crowded elevator even though it was carrying a large item.
Various complaints arose, such as having to call again after departure, and these were communicated to the building owner, manager, etc.

Once the building has been delivered, in order to respond to the above complaints, elevator users such as building owners and managers must request modification from the elevator manufacturer, and the elevator manufacturer must modify the program. I had to make additions and rewrite the ROM. The reality is that this requires a lot of manpower and time, and furthermore, it is impossible to satisfy all the diverse demands of users, such as passengers, building owners, and managers. However, there is also the problem that it is difficult to present the effects of actually operating the elevator after changing the program.

An object of the present invention is to solve the above problems by inputting the user's request in an easy-to-understand format called sensibility, directly incorporating it into the control system, and immediately reflecting it in the control. Furthermore, it is an object of the present invention to provide an elevator group management control device that can easily add or delete various user request items.

[Means to solve the problem]

The above object is to enable a user to easily set a qualitative request for elevator operation as a sensory goal using a sensory goal input means, and to convert the input sensory goal into an actual elevator control goal; This is achieved by providing a control execution means that executes actual group management control using these control targets.

Specifically, the emotional goal setting means sets multiple emotional goals and the elevator usage environment (elevator operating conditions, traffic demand, etc.), and the goal conversion means sets the emotional goals based on the predetermined items of the emotional goals. A conversion function (corresponding to a membership function of fuzzy control) is provided for each environment in which the elevator is used, and this conversion function is used to convert the elevator into a control target.

Furthermore, the control execution means includes means for selecting at least one control method candidate for achieving the control target, means for determining predicted achievement values of each control target for the selected control method candidates, and a means for determining the predicted achievement value of each control target for the selected control method candidate. The present invention is characterized by comprising means for determining a control method based on the achieved value.

Further, the result of actually controlling each elevator is inversely converted by the target converting means, and the result is notified by the sensory target setting means.

[Effect]

Inputting emotional goals (i.e., value windows, interests, preferences, sensations, likes and dislikes, etc.), which are qualitative requirements for elevator operation, can be done using plain Japanese or laser charts, etc. It can be easily set even when not at home, and the set emotional goals are converted into control goals using variable functions obtained through questionnaire surveys and the like.

By replacing the multiple control objectives that are correlated with each other with control methods based on preset rules, we fully incorporate user requests and realize group management control that is unique to each building. can.

〔Example〕

An embodiment of the present invention will be described below with reference to FIGS. 1 to 18.

FIG. 1 shows the overall configuration of an elevator group management control device according to the present invention. The group management control device of the present invention is mainly composed of three blocks.

One is a sensory goal setting means 2 that sets the user's sensory target value and the elevator usage environment such as the elevator operating condition and traffic demand to achieve the sensory target value. By providing this means, even people who are not experts in elevators can easily change the control method, make operation reservations, etc. In this figure, an input terminal (personal computer, workstation, etc.) 2-1 that combines a keyboard and a display is used to input predetermined conditions 2-1 such as sensitivity target values.
2 is input, but instead of this, it is also possible to provide a dip switch or the like in the group management control device main body 1 and change the setting conditions by turning the switch on and off. Furthermore, it is also possible to use a telephone line or to directly set the settings in the group management control device main body 1 using a recording medium such as an IC card. The other block is the emotional goal setting means 2.
It converts user requests (sensitivity target values) set in For each sensitivity item, a target conversion function created based on data obtained through questionnaire surveys etc. from users is extracted using A target value is determined, and a control method that best achieves the control target is determined. The determined control method is stored in a table classified according to each condition. Note that this target converting means 3 may be provided outside the group management control device main body 1 instead of inside, or may be integrated into the sensory target setting means 2. In the next block (control execution means 4), the operating status of elevators, etc. is determined based on the data from the hall call control unit 5 and each machine control unit 6, 7.8, and the control execution unit stored in the table is The method and call assignment method are extracted and executed, and the results are transmitted to each machine. By configuring the system in this way, user requests can be quickly reflected in the control, improving the usability of the elevator. Furthermore, by converting the actual driving results of each machine into a sensory target value using the target converting means 3, it is also possible to inform the user of the extent to which the user's movements have satisfied the set target.

FIG. 2 is a diagram illustrating the operations of the emotional goal setting means 2 and the goal converting means 3. The sensory goal setting means 3 includes a sensory target value setting section 2a and an elevator usage environment (for example, time of day, traffic volume, etc.) in which the sensory target value must be achieved.
and an elevator usage environment setting section 2b that sets the usage status of the elevator, the nature of the building in which the elevator is installed, the specifications of the elevator, etc. Incidentally, the emotional target value does not directly set the desired target value of the user as a physical quantity, but indirectly indicates the degree of psychological sensation such as the strength or weakness of preference. In other words, it can be said that it is a qualitative request for elevator operation that is derived from the user's value window, interests, preferences, senses, likes and dislikes, etc. For example, if you are not an elevator expert (designer, maintenance engineer, etc.), even if you say, ``I want to get on the train quickly,'' you might say, ``I want to get on the train quickly.'' It is difficult to make a request with a quantified value such as "I would like the waiting time to be faster than 00 seconds because the appropriate waiting time is around 00 seconds." So, ``I want to ride in the empty car.''
The present invention attempts to solve the problem by introducing qualitative target values such as "I want to ride quickly" as emotional target values.

However, even if the elevator user makes a request to completely satisfy all input items such as "I want to ride in an empty car", "I want to get on quickly", etc., there are conflicting input items t1 (for example, Considering driving efficiency, etc., it is difficult to simultaneously satisfy the desire to ``get into an empty car'' and the desire to ``get on the car quickly'' during busy hours. It is necessary to set the priority in advance, and then rank it. (This ranking is possible because it is a matter of comparison, no matter how qualitative the target value is.) The first method for determining this priority is the input ranking. Possible methods include a method in which the order in which the emotional goals are input is used as a ranking, and a second method that allows the ranking to be set at the same time as setting the emotional goal values.In addition to this priority order, it is also possible to add weights. It is even more effective if priority and weighting are used together.

Furthermore, since the sensitivity target value is a qualitative target value and simply expresses the user's desired size, this input sensitivity target value is converted into an actual control target value (control amount). Otherwise, the elevator cannot be controlled. However, when converting this goal, the sensitivity target value alone is not uniquely determined, so in addition to inputting this sensitivity target value,
Elevator usage environment (elevator specifications such as number, speed, capacity, etc., building specifications such as hotels, company-owned buildings, department stores, multi-tenant buildings, etc., 2 seasonal time periods (or hours)
(1st floor floor, traffic volume, etc.) will be manually checked. The control target determination unit 3a in the target conversion means 3 determines the function or rule used for target conversion according to the elevator use environment.
At the same time, the control target value corresponding to the sensitivity target value is determined, and the value is recorded for each item in the control target table 3b. A specific method for converting this control target will be described later.

In Figure 2, the sensitivity target value is set as a numerical value from 1 to 5, but instead of this input method, as shown in Figures 3 and 4, you can use a radar chart or a mouse, etc. It is also possible to set it analogously. FIG. 3 shows an example of a hotel's sensory goals, which are set in advance by a designer or the like based on the usage status of elevators, etc. As shown in this figure, when guests use the elevator at a hotel, they do not want to meet other people as much as possible, or they want to ride in an empty car because they have baggage, etc. Demands such as ``I want to be informed of arriving carts correctly'' are large due to the desire to minimize the amount of transportation carried by cars, while requests such as ``I want to ride quickly'' and ``I want to transport many people in a short time'' are small. However, at some point, an event or the like may occur and there may be a demand for ``transporting many people in a short period of time.'' At this time, it is no longer possible to satisfy the request values for other items such as "I want to ride in an empty car" as in the past. The degree of this change changes depending on the amount of demand and importance of each item. The degree of importance of achieving this requirement is input by ranking in Figure 2, but there is also a method of having people rank it using a radar chart like the one shown in the figure, and a method of determining the set ranking as a ranking of importance. can also be considered. Figure 4 shows an example of the sensitivity goals for a building occupied by five companies. In the case of this diagram, considering work efficiency, ``I want to be notified of reservation carts as soon as possible'', 2 ``I want to transport many people in a short time'', ``
Requests for the item "I want to get on the train quickly" tend to be smaller.

By the way, it is necessary to set the specifications of the building in accordance with the sensitivity input, but when the properties of the building are shown in a radar chart, it can be seen that there are differences in the properties depending on the purpose as shown in Figure S. The solid line in Figure 5 represents the properties of the buildings occupied by the five companies. (b)
The dotted line represents the characteristics of the hotel, and the difference in these characteristics is the reason for the difference in the above-mentioned sensitivity target values.

FIG. 6 shows a configuration for converting the set sensitivity target value into a control target value.

As described above, when setting the sensitivity target value, the elevator usage information is also set in the elevator usage environment setting section 2b. This elevator usage information can be roughly divided into building properties 2bl, elevator specifications 2b2, and usage information 2b3. Once set, the specifications of the elevator and the nature of the building will not change significantly, but usage information 2b3 includes items that must be re-set whenever the user sets new requirements. (For example, items such as traffic volume and time zone 9th floor that need to meet new requirements). The emotional goal set by the emotional goal setting section 2a (not shown) and the elevator usage information set by the elevator usage environment setting section 2b are sent to the control goal setting section 3a of the goal converting means 3. The target conversion means 3 includes a control target setting section 3a (control target conversion function generation rule 3a1. conversion function database 3a2. target conversion section 3a3) and a control target data table 3b. Here, the control target conversion function generation rule 3a1 starts a conversion function selection rule set for each property of the building from elevator usage information, and generates a conversion function database 3a.
Conversion function item Sl corresponding to the emotional target item recorded in advance in No. 2.

S2...Selects the functions fsl...fsm in Sn.

FIG. 7 shows an example of a conversion function. This corresponds to a fuzzy control membership function or the like. 7th
In the figure, for example, f ta (x t) or f x b (
xt) (where fta(xi) is a function when there is a hall information guide device, and f 1b(x t) is a function when there is no hall information guide device) is selected. In other words, taking into consideration the environment in which the elevator is used, whether there is a hall information guidance device or not, rIF is determined using the control target conversion function generation rule 3al.
There is no hall information guidance device, AND I want to board quickly.
THEN fl(x)=fib(xt) J is searched for and the control target conversion function fxb(xt) is selected. Similarly, conversion functions are selected for the sensory goal items ``I want to ride in an empty car'' and ``I want to arrive early'' in consideration of the usage environment of each elevator.

In addition, in the example shown in FIG. 7, for the sake of clarity, there is only one type of judgment item for the elevator usage environment.
In reality, the conversion function to be used is determined by a combination of multiple items.

Next, an example will be shown in which the sensitivity target value is converted into the control target value using the above conversion function.

In Fig. 7, suppose that the sensitivity target value of "I want to ride quickly" is set to 4 at the time of goal setting, and the conversion function is also selected as f 1 (x) = f tb (xz) according to the generation rule. From the conversion function, a target value x1 of the waiting time is specifically calculated as xt=40 seconds as a control target value. This calculated value of 40 seconds is the maximum allowable waiting time (limit value)
It is determined that the waiting time is 40 seconds or less and is recorded in the control target table 3b. In addition, the usage environment and weighting of the elevator, which must naturally achieve this control target, are also included in this control target table 3b.
recorded in In this way, qualitative and indirect sensitivity target values are converted into quantitative and direct control target values.

FIG. 8 shows an example of control target items corresponding to emotional target items. In Figure 8, sensory goals and control goals are described as having a one-to-one correspondence, but in reality, one sensory goal influences multiple control goals (for example, "I want to get on the train quickly"). In order to satisfy the criteria, not only the waiting time but also the first-come-first-served ratio of car calls and the amount of information provided have a major influence.)
.

A plurality of control target values determined by the above method are transmitted to the control execution means 4 (see FIG. 1). The control execution means 4 shown in FIG. 9 uses control methods (for example, minimum waiting time allocation control (Min)) that may be realized based on the information in the control target table 3b.

Maximum waiting time minimization allocation control (M in-M a x
), average waiting time minimization allocation control, floating service control, etc.) are derived using the knowledge (control method selection rules) in the knowledge base 4e. (If there is only one control method that can be realized, then that is the control method to be determined.)
Several control method candidates derived in this manner are sent to an elevator simulation experiment section 4g that simulates the movement of the elevator using software. The simulation experiment section 4g extracts data such as traffic volume and elevator specifications from the control target table 3b, performs simulation experiments using a plurality of selected control methods, and uses the results for each control target item. and calculate the predicted achievement value for each control objective.

The obtained preal'l achievement value is transmitted to the multi-goal decision making section 4h, where it is compared with the previously determined control target value and the control method with the highest degree of achievement is selected.

This comparison of superiority and inferiority can be done, for example, by determining the overall target △, the predicted achieved value as a whole as the predicted achieved value f of each control target, and Peltle f= with (i = 1...n) as an element. (ft, fz . . . fn), and a control method that provides a small distance of the predicted achieved value vector f from the target Δ value vector f is selected. The control method selected in this manner is stored in the control method database 4f for each elevator usage information.

Now, next, we will explain the online operation. In the control execution means 4, the signal S2 from each car control section 6 to 8 and the signal S1 from the hall call control section 5 are input to the elevator operation data collection section 4a. elevator
The operation data collection unit 4a uses the input data to collect elevator usage information data (traffic demand data, elevator position and direction, assigned call, car car) for a short period of time (from about 10 minutes before a new hall call occurs). number of passengers (passenger rate), etc.). The data obtained here is sent to the learning system 4b (iS3).

The learning system uses this data to learn traffic demand by time of day, waiting times, and other data. Using the learned information S5 and the short-term usage information S3 created by the data collection unit 4a, the control method selection unit 4d selects the elevator
Determines the driving status of the vehicle.

Further, in this control method selection section 4d, as described above, the control method selection knowledge base 4e, the simulation experiment section 4g, and the multi-objective decision making section 4h determine the control method selection for a plurality of control target values input in advance. From the control method database 4f in which control methods have been stored, a control method suitable for the actual operating condition of the elevator is selected using control method selection rules.

The control method selected here is sent to the group management control system 4C.
4. Here, each machine is evaluated using the transmitted control method to determine the selected machine, and the new hall call sends an assignment command to the selected machine.1. j S 2.

FIG. 10 shows an example of a call allocation control method selection rule. As shown in the figure, the rule table is composed of three parts. Tll is a registered rule table that indicates whether or not rules to be applied in each direction of each floor are defined, and rules are defined where an O mark is placed between them. In this example, rule 3 is applied to the first floor ascending call.
is registered, and rule 1 is applied to the call to ascend to the third floor.
This shows that Rule 3 is registered.

Other parts marked with an O mark indicate that the rules for each of the above explanations and the same article have been registered. T
12 is a rule condition table in which the condition part of each rule is recorded. The conditions include specifying the day of the week, 2 times of the week, traffic demand, etc. corresponding to elevator usage information, and control target values (waiting time, 2 occupancy rates, etc.).

Call notification time etc) is set. All of these conditions are treated as AND conditions, and when treated as OR conditions, they are treated as ``1H'' as a separate rule. Each of these data is written in a judgment condition expression. For example, the condition that the occupancy rate is 30% or less is WE I GHT(K)=<SEK I SA I (
K) I O, 3... (1) However, WE IGHT (K)
: The number of passengers on board K is described in 5EKISAI (K): as the capacity of the car.

T13 is a rule execution table that records the execution part when the conditions of each rule are satisfied, and records the evaluation formula or assigned machine number. For example, the evaluation formula for selecting the elevator that can arrive the earliest from elevators with a capacity of 30% or less is: ELSE VALUE (K) = MAX
J...('HASIGN=K FORMINE[VALUE(K)
]...(3) However, VALUE(K): Array K of evaluation values
: Variable corresponding to the machine number A S I G N : Assigned machine number MAX
: Described as maximum value. The data actually recorded in each table is obtained by converting each of the above equations into binary data that can be executed by a microcomputer. Also, a blank field means that there is no condition.

The operations described above are shown in a flowchart as shown in FIG. 11. First, the elevator usage environment is set (EIO). Subsequently, a sensitivity target item corresponding to EIO is selected and a target value is set (E20). According to the set elevator use environment and sensory goal, start the control target conversion function generation rule and find the conversion function (E30)
However, if the control target value is uniquely determined, the control target value is determined by the generation rule. Subsequently, the sensitivity target value is converted into a control target value using the conversion function selected at E30 (E40). The converted control target value is recorded in the control target table (E50). From here, the work is transferred to the control execution means 4. Control method candidates are selected using the values in the control target table and the knowledge of experts set in advance (GIO). The selected plurality of control methods are transmitted to the simulation experiment section, and the elevator is operated in a simulated manner according to the set conditions using a software-based system that simulates the operation of the elevator (G20). A predicted achievement value for each control item is calculated from this operation result (G30). The predicted achievement value of each control method is compared with the input target value using the multi-goal decision-making method, and the control method with the best degree of goal achievement is selected (G40). The control method may be presented to the user, and if the user is not satisfied with the control method, the user may repeat the emotional target setting E20 to G30 to select the best control method.

The selected control method is stored in the control method data table together with the elevator usage information (G50). As described above, the processing from ELO to E50°GIO-G50 can be done offline from the perspective of elevator control.

Next, the elevator operation control is started by the elevator control execution start command LIO. First, the processing of the call signal for each landing, that is, the landing call input processing is executed (L20). Furthermore, a communication process for exchanging various data from each machine control system is executed (L30).

Usage information is obtained based on these data and the like, and the control method to be used is selected from the control method database using the obtained usage information (L40). Next, the optimum call allocation car is determined by the selected control method and call allocation processing is executed (L50). Based on each hall call assignment information, estimated elevator arrival time, etc., the guidance content on the guidance display of each hall is determined and notification processing is performed (L60). In addition to the above processing, processing such as outputting and displaying various data (L70
).

Next, after completing this series of tasks, it is determined whether or not to continue the operation (L80), and if the operation is to be continued, L2
If the process of 0 is repeated again and the operation is terminated, the operation is terminated.

Using FIG. 12, a schematic flow of the process visible to the user in the flow shown in FIG. 11 will be shown. First, when the user turns on the switch, a screen (e.g., Figures 3 and 4) in which initial emotional goals are set is displayed (EO).
. Next, the user inputs the target value of the target to be changed on the initial setting screen using a mouse, etc. (E20)
. After inputting all the change values (transmitting a change completion signal), the sensory target is converted into a control target using means such as a conversion function (E40). Next, control method candidates that are likely to best achieve each control objective are selected using the control objective table and knowledge base (GIO).

There may be one control method candidate or multiple control method candidates selected here, so it is necessary to determine whether there is only one control method candidate or multiple candidates (G15). If there is only one control method candidate, that method can be immediately It is sent to section G20'.

The simulation section G20' executes a simulation using the traffic flow data set at the time of inputting the sensitivity target. From the experimental results, a predicted achievement value of the previously set control target is determined (030'). The result is reversely converted into an emotional goal and displayed together with the emotional goal previously set by the user (G45').

On the other hand, when multiple control methods are selected, simulation experiments are conducted for each control force method (G20
), and as a result, a predicted target achievement value for each control target is calculated for each control method (G30).

Next, the calculated predicted target achievement value and target value are compared, and the overall achievement level is calculated for each control method (G35).

This overall degree of achievement is compared for each control method, and the one with the largest (or smallest) degree of achievement is determined as the optimal control method (G40).

The predicted target achievement value of the selected control method is inversely converted into a sensory target value and displayed together with the sensory target value previously set by the user (G45). This display screen allows the user to
If it is determined that the control method determined by the system is sufficient (G6
0), send the method to the control method table (G70
). If you decide that this method is not good, try E20 again.
Repeat from

Next, the off-line processing from inputting a sensory target to recording a control method in a data table will be described based on a specific example.

First, the Hotel 5 elevator specifications (number of elevators, speed, service floors, etc.) are set as building specifications for the elevator usage environment as shown in Figure 13, and furthermore, the reference floor ( Suppose that there is a normal traffic volume on the front floor) and a check-in time period has been set (E10 in Figure 11).

At this time, assuming that the emotional target items are the six items shown in FIG. 14, it is assumed that the values shown by the solid line are set in advance as initial values on the system side. (Of course, it goes without saying that the configuration may be configured such that the user sets the die reflex l-.) In this figure, the user can use an input means such as a mouse to enter the emotional target value of ``I want to ride quickly.'' Suppose that you change the setting from the value 1 to the value 4 (010 in Figure 11).At the same time as this setting change, also input the priority of achievement.If the priority of achievement is set by default, As in the case, if the priority of the item for which a setting change is requested is low, the control method that can be achieved will not change, so the customer is prompted to change the priority.Here, by changing the setting, the target value is lower than the initial setting value. If it becomes large, put it first in priority order,
If it becomes smaller, the priority will be moved to the sixth (last) position.

Next, a control target conversion function generation rule is activated to convert the sensitivity target value of "I want to ride quickly" into a control target value. An example of this rule (for hotels) is shown below.

1) Rule group rule I for the item “I want to board early” IP hotel AND check-in time T HE N f 1 (X) = f xh (x t) Rule 2 IF hotel AND lunch time T HE N f t (x ) = f th(x 2)
A target conversion function with conditions matching the rule is selected (010 in FIG. 11). This selected target conversion function (here, it is assumed that fxh(xt) in FIG. 15 has been selected) is sent to the target conversion means 3, where a control target is calculated. In other words, since the initial sensitivity target value was 1, the waiting time was previously set to 40 seconds or less, but with this setting, the sensitivity target value was set to 4, so this target value was reduced to 25 seconds. It is set as follows (010 in Fig. 11). The previously set control target table value is changed based on this target value (E50 in FIG. 11).

At this time, the weight of the control target table is also changed.

FIG. 16 shows the state before and after the current control target change.

Control method candidates that satisfy these control objectives are selected using a knowledge base that has been set in advance based on the knowledge of experts (FIG. 11, 010). An example of this selection rule is shown below.

Rule IF time zone = Tland traffic volume ≧ a and front floor T H E Nφ = T t Rule 2 IF time zone = Tland traffic volume ≧ a and general floor TH
ENφ=T2 Here, T1 is the check-in time period, the traffic volume is a person/vehicle, and
5 minutes are shown, and Tl and T2 show the call allocation method. Here, the call allocation method T1 is the minimum waiting time allocation method (Min), and its evaluation value is determined by the following equation.

To φ=TK-α0TAK+α' ′TBK −
(4) T1:=nin(φ11 ””...φK)
-(5) Here, φ is taken into account. Second, the hall waiting time evaluation value of the machine is T: The time required for the machine to arrive at the newly allocated hall call floor TAK: The time taken for the machine to arrive at the newly allocated hall call floor is taken into account. Stop call evaluation value TBK: Load concentration evaluation value α, α' depending on the elevator condition. Doubleness coefficient. Next, T2 is the longest waiting time minimum call assignment method (M
i n -M a x), and is determined by the following formula.

φKl=TKl+Tpl-α・TAKI+α'TBKI
...(5) φKl: Evaluation value T of the 1st floor hall call assigned to the K machine Time from the current time until the machine arrives at the 1st floor Tpt: Time from the time the 1st floor hall call occurs Transfer time TAKtCK Stop call evaluation value TBKI: Load concentration evaluation value α, α′ according to elevator status Duplex coefficient φx=max (1 for φ. “””φKl)
°°° (6) T 2 = min (φ above, φ2
"'"'φK) = 17). In other words, calculate the evaluation value for each hall call assigned to each machine (Equation (5)), select the maximum evaluation value (Equation (6)), and call the one with the minimum evaluation value. It is something that is assigned.

In addition, rules for selecting formalized allocation evaluation methods are prepared in the knowledge base, such as the average waiting time allocation evaluation method, the waiting time distribution allocation evaluation method, the 2-equally spaced car allocation evaluation method, and the evaluation method that combines these evaluation methods. has been done.

Now, in this control method selection rule, in addition to the call assignment method, various operating specifications are also selected. In the hotel example mentioned above, a lobby control method is also commanded to return the elevator, which does not have a call reception, to the standard floor. Here, it is assumed that as a result of the user inputting the sensitivity target value, two control methods, the minimum waiting time evaluation method and the average waiting time evaluation method, are derived as possible to be realized. In addition, in the initial setting on the system side, the initial set target value was obtained by the longest waiting time minimum call allocation method that suppresses the occurrence of long waiting times. However, since the minimum waiting time allocation evaluation method and the average waiting time allocation evaluation method were selected as candidates, the selected two
The type of call allocation evaluation method and operation specifications are sent to the simulation experiment department and a simulation experiment is conducted (020 in FIG. 11). As a result, results obtained using the two types of allocation evaluation methods and other operating specifications are obtained. If only the allocation evaluation method is changed this time, the predicted achievement values for each control target can be obtained as shown in FIG. 17 (030 in FIG. 11). From this result, we will calculate Q for each allocation method using the multi-objective decision-making method, which is one of the methods for evaluating the goal achievement value described above. This time, as a method for evaluating the target achieved value, the value of the item that satisfied the set target value is evaluated as zero, and the unachieved value is multiplied by each weighting coefficient value, and the magnitude of the target unachieved value is calculated. Find it with Also, the weighting coefficient ω.

Let be the weight set at the time of setting each control target. In front of
The degree of achievement is determined for each control method shown in FIG. 17, which was previously obtained through a simulation experiment. For example, the achievement level QPI for the minimum waiting time method is as follows.

R-t=8(40-30)+7(5-3)+6(3-3
)+9(25-25)+5(-35+30)+4(0,
1-1) In the above formula, the 1st item is the occupancy rate, the 2nd item is the reservation change rate, the 3rd item is the first-come-first-serve rate, the 4th item is the hall waiting time, the 5th item is transportation capacity, and the 6th item is the reservation notification time. . Here, the target value of transportation capacity for 5 items is 30 people/11in or more,
The equations for addition and subtraction are different because it is better if it is larger than the target value, and the smaller the remaining terms are than the target value. Qpl is determined using the above conditions.

Upi=8X10+7X2+6XO+9XO+5XO+
4XO=94. Similarly, when calculating the average waiting time method, Qp
2=147. As mentioned above, this time, in order to make the explanation easier to understand, the negative term was set to zero, but in reality, the weighting coefficient ω1 for each evaluation item was used as a coefficient for normalizing each control item, and this time the blade and There is also a method of evaluating in addition to the evaluation value the good achievement rate you set.

As a result, the call allocation/assignment method with the smallest waiting time is selected. The control target value of the selected control method is again converted back into a sensory target and displayed together with the initial setting value in the form of a radar chart (dotted line in FIG. 14). If the user determines that this method is acceptable, the selected control method is registered and recorded in the control method data table.

The processing up to EIO-050 in FIG. 11 has been described above using a specific example. The explanation so far has been based on the assumption that all processing is performed within the group management control device. Another embodiment is shown in FIG.

This embodiment consists of a sensory goal setting support system 9 and a group management control device 1, and the group management control device is the multi-goal decision making means 4h of the control execution means 4 described above.

The parts are the same except for the simulation experiment section 4g and the knowledge base 4e. That is, the off-line operation part is taken out and made into a separate device.

The sensory goal setting support system 9 includes a sensory goal input/output section 2a' corresponding to the aforementioned sensory goal setting means 2, an elevator usage environment input setting section 2b', and a control target conversion function generation unit corresponding to the goal conversion means 3. The rule 3al, the conversion function database 3a2, the target conversion unit 3a3, the control method selection rule 4he that combines the multi-purpose decision making unit and the knowledge base, which were included in the control execution unit 4, the simulation experiment unit 4g, and the control method It consists of a database section 4f.

Here, the function is to determine a control method that satisfies a plurality of input sensory goals, and to record the determined control method in a control method database within the group management control device. With this configuration, user requests can be input in the form of sensitivities and converted to control values completely separately from the main body of the group management control device, so, for example, the sensibility target setting support system can be connected to a handheld computer (laptop). etc.) and various terminal devices in all buildings where elevators are installed.
This has the effect of allowing meetings to be held with users even when they are far away.

Furthermore, as another embodiment, if the control target value can be directly inputted in advance, it is also possible to have a configuration in which the sensitivity target value setting and the conversion unit to the control target are removed.

〔Effect of the invention〕

According to the present invention, in order to automatically convert an elevator user's sensory goals (qualitative quantities) into actual control goals, a desired control method is executed without the help of an elevator expert. It becomes possible to do so. Furthermore, regarding the results of actually operating the elevator after delivery, we first check whether the control desired by the user is being executed or not, and use the operating data to convert it into a sensory target or control target value. It is also possible to diagnose the elevator usage situation. moreover,
Since the control method used by the control execution means is adopted after the user is satisfied with it, the usability for the user is improved.

[Brief explanation of the drawing]

FIG. 1 is an overall configuration diagram of an embodiment of the present invention, FIG. 2 is an explanatory diagram of the operation of the emotional goal setting means and goal conversion means, FIGS. 3 and 4 are examples of emotional goal setting, and FIG. Laser Char 1-1 showing the properties of a building Figure 6 is an explanatory diagram of the control target conversion method, Figure 7 is an example of a target conversion function, Figure 8 is a correspondence diagram between sensory targets and control targets, Figure 9 10 is an example of a control method selection rule, FIG. 11 is an operation flowchart of the present invention, FIG. 12 is a flowchart of the part visible to the user, and FIG. 13 is an elevator diagram.
Specification setting example, Figure 14 is an example of sensitivity target setting change, Figure 15
16 is an example of a control target table, FIG. 17 is an example of a predicted achieved value, and FIG. 18 is an overall configuration diagram of another embodiment of the present invention. 1... Group management control device, 2... Sensitive goal setting means,
3...Target conversion means, 4...Control execution means, 5...Hall call control section, 6, 7.8... Machine control section.

Claims (1)

[Scope of Claims] 1. In an elevator group management control device that performs group management control of a plurality of elevators in service between multiple floors, a sensory goal setting means for setting qualitative requirements for elevator operation as a sensory goal; An elevator group management control device comprising: a target conversion means for converting a set emotional target into an elevator control target; and a control execution means for executing actual group management control using the control target. . 2. The sensory goal setting means sets a plurality of sensory goals and the elevator usage environment, and the goal conversion means converts a conversion function for each elevator usage environment into a predetermined item of the sensory goals. 2. The elevator group management control system according to claim 1, wherein the elevator control target is converted into an elevator control target using the conversion function. 3. The control execution means includes means for selecting at least one control method candidate for achieving a control target, means for calculating a predicted achievement value of each control target for the selected control method candidate, and 3. The elevator group management control device according to claim 2, further comprising means for determining a control method based on a predicted achievement value of. 4. The control execution means collects the results of actually controlling each elevator, and the target conversion means inversely converts the control results into a sensitivity target value, which is then reported to the sensitivity setting means. The elevator group management control device according to claim 1. 5. The elevator group management control system according to claim 1, 2 or 4, wherein a laser chart is used in setting the sensitivity target.