Patent EP0511904A2 successfully refreshed from Google Patents.
EP0511904A2
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EP
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Elevator dispatching
Assignee: Otis Elevator Co
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Filing: 1992-04-23
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Granted: —
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Expires: 2012-04-23
Abstract
Abstract Elevator control software uses a signal from a passenger weight sensor and observed weight fuzzy logic sets to provide a fuzzy logic set indicative of the number of passengers in a car. 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 utility of assigning each car of an elevator system to service a hall call is determined by estimating the performance of each car using a plurality of performance criteria. The number of hall passengers waiting at a stop for service by a car is determined by first calculating instantaneous passenger rates whenever a hall call button is pressed or whenever passengers board a car. An uncertainty filter is provided with input data indicating a fuzzy logic set having basis elements corresponding to cars of an elevator system having degrees of membership associated therewith corresponding to the utility of assigning the associated car to service a hall call.
Inventors
- 👤 David J. Sirag, Jr.
- 👤 Paul T. Weisser, Jr.
Bibliographic Details
Application Number
—
Jurisdiction
EP
Data Source
google_patents
Last Synchronized
2026-11-10 01:46
CPC Classifications
B; B66; B66B; B66B1/00; B66B1/34; B66B1/3476; B66B1/24; B66B1/2408; B66B1/2458; B66B1/3484; B66B2201/00; B66B2201/10; B66B2201/102; B66B2201/20; B66B2201/211; B66B2201/214; B66B2201/222; B66B2201/40; B66B2201/401; B66B2201/403
Claims Analysis
Total Claims: 34
Claim 1
Independent Claim
155 words
A method of determining the number of car passengers, comprising the steps of: asserting a weight signal indicative of passenger weight; providing a plurality of observed weight fuzzy sets, each set corresponding to a particular number of passengers, wherein for each of said observed weight fuzzy sets, the degree of membership of each term corresponds to the frequency of occurrence of a particular value for the magnitude of said weight signal; and forming a passenger count fuzzy set, indicative of the number of car passengers, wherein for each term the degree of membership equals the degree of membership of a term of a particular one of said observed weight fuzzy sets having a basis element corresponding to the magnitude of said weight signal and wherein the basis element for each term of said passenger count fuzzy set is indicative of a number of passengers represented by the particular one of said observed weight fuzzy sets.
Claim 2
Dependent Claim
34 words
A method of determining the number of car passengers, according to claim 1, further comprising the step of: defuzzifying said passenger count fuzzy set to produce a single crisp value for the passenger count.
Claim 3
Dependent Claim
48 words
A method of determining the number of car passengers, according to claim 2, wherein said defuzzification is performed by setting the single crisp value of the passenger count equal to the basis element of the term of the passenger count fuzzy set having the highest degree of membership.
Claim 4
Dependent Claim
46 words
A method of determining the number of car passengers, according to claim 1, further comprising the step of: normalizing said passenger count fuzzy set by dividing the degree of membership of each term by the sum of the degrees of membership of all of the terms.
Claim 5
Dependent Claim
34 words
A method of determining the number of car passengers, according to claim 4, further comprising the step of: defuzzifying said passenger count fuzzy set to produce a single crisp value for the passenger count.
Claim 6
Independent Claim
345 words
A method of constructing a table having indices indicative of passenger weight and having entries indicative of passenger count, comprising the steps of: a first step of providing a plurality of observed weight fuzzy sets, each set corresponding to a particular number of passengers, wherein for each of said sets, the degree of membership of each term corresponds to the frequency of occurrence of.a particular value of the magnitude of said weight signal; a second step of setting a weight variable to zero and a passenger count variable to zero; a third step, following said first and second steps, of forming a passenger count fuzzy set, indicative of the number of car passengers, wherein for each term the degree of membership equals the degree of membership of a term of a particular one of said observed weight fuzzy sets having a basis element corresponding to the magnitude of said weight signal and wherein the basis element for each term of said passenger count fuzzy set is indicative of a number of passengers represented by the particular one of said observed weight fuzzy sets; a fourth step, following said third step, of defuzzifying said passenger count fuzzy set, by normalizing said set, multiplying the degrees of membership of terms of the normalized set by basis elements of said set, and by summing the result of said multiplication to produce a single crisp value; a fifth step following said fourth step, of comparing said weight variable and the result of said fourth step and, if said fourth step results in a value different from the value of said weight variable, entering the values of the weight variable and the passenger count variable in the table and setting the value of the weight variable to the value obtained from said fourth step; a sixth step, following said fifth step, of incrementing said weight variable by a predetermined incremental amount; and a seventh step, following said sixth step, of performing said third, fourth, fifth, and sixth steps until the value of said weight variable exceeds a predetermined maximum amount.
Claim 7
Dependent Claim
38 words
A method of constructing a table having indices indicative of passenger weight and having entries indicative of passenger count, according to claim 6, wherein said predetermined incremental amount corresponds to the granularity of an elevator load weighing device.
Claim 8
Dependent Claim
169 words
Apparatus, for determining the number of car passengers, comprising: means for asserting a weight signal indicative of passenger weight; means for providing an observed weight signal indicative of a plurality of observed weight fuzzy sets, each set corresponding to a particular number of passengers, wherein for each of said sets, the degree of membership of each term corresponds to the frequency of occurrence of a particular value for the magnitude of said weight signal; and means, responsive to said weight signal and said observed weight signal, for asserting a fuzzy passenger signal indicative of a passenger count fuzzy set wherein for each term the degree of membership equals the degree of membership of a term of a particular one of said observed weight fuzzy sets having a basis element corresponding to the magnitude of said weight signal and wherein the basis element for each term of said passenger count fuzzy set is indicative of a number of passengers represented by the particular one of said observed weight fuzzy set.
Claim 9
Dependent Claim
45 words
Apparatus, for determining the number of car passengers, according to claim 8, further comprising: means, responsive to said fuzzy passenger signal, for defuzzifying said passenger count fuzzy set to provide a passenger count signal indicative of a single crisp value for the number of passengers.
Claim 10
Dependent Claim
33 words
Apparatus, for determining the number of car passengers, according to claim 9, wherein said defuzzification is performed by selecting the term of the passenger count fuzzy set having the highest degree of membership.
Claim 11
Dependent Claim
64 words
Apparatus, for determining the number of car passengers, according to claim 8, further comprising: means, responsive to said fuzzy passenger signal, for providing a normalized passenger count signal by dividing the degree of membership of each term of said passenger count fuzzy set by the sum of the degrees of membership of all of the terms to produce a normalized passenger count fuzzy set.
Claim 12
Dependent Claim
50 words
Apparatus, for determining the number of car passengers, according to claim 11, further comprising: means, responsive to said normalized passenger count signal, for defuzzifying said normalized passenger count fuzzy set to provide a passenger count signal indicative of a single crisp value for the number of passengers in the car.
Claim 13
Dependent Claim
54 words
Apparatus, for determining the number of car passengers, according to claim 12, wherein said means for defuzzifying is comprised of: means for multiplying the degree of membership of each term of the passenger count fuzzy set by the basis element of each term; and means for summing the results achieved by said multiplication step.
Claim 14
Dependent Claim
57 words
In a method of assigning a car to service a hall call, the step of assigning a car by choosing a term from a fuzzy set having a basis set corresponding to cars of an elevator system having degrees of membership associated therewith corresponding to the utility of assigning the associated car to service the hall call.
Claim 15
Dependent Claim
34 words
In a method of assigning a car to service a hall call, according to claim 14, wherein said assigning step requires choosing a term from said fuzzy set having the highest degree of membership.
Claim 16
Dependent Claim
38 words
In a method of assigning a car to service a hall call, according to claim 15, wherein said assigning step requires choosing a term from said fuzzy set having a degree of membership above a constant, predetermined value.
Claim 17
Dependent Claim
34 words
In a method of assigning a car to service a hall call, according to claim 15, wherein said assigning step requires choosing a term from said fuzzy set after a predetermined amount of time.
Claim 18
Dependent Claim
39 words
In a method of assigning a car to service a hall call, according to claim 15, wherein said assigning step requires choosing a term from said fuzzy set which exceeds a value which changes as a function of time.
Claim 19
Dependent Claim
162 words
Method of determining the utility of assigning each car of an elevator system to service a hall call, comprising the steps of: forming a performance fuzzy set for each cars, said performance fuzzy set having basis elements corresponding to a plurality of performance criteria and having degrees of membership corresponding to the performance of each of said cars measured in terms of the associated performance criteria; scaling the degrees of membership of terms of each of said performance fuzzy sets by a plurality of values indicative of the importance of each of said performance criteria, thereby forming a plurality of scaled performance fuzzy sets; and forming an assignment utility fuzzy set having basis elements corresponding to the cars of the elevator system and having degrees of membership corresponding to the utility of assigning the associated car wherein each term of said assignment utility fuzzy set equals the term from one of said scaled performance fuzzy sets having the maximum degree of membership.
Claim 20
Dependent Claim
165 words
Method of determining the utility of assigning each car of an elevator system to service a hall call, comprising the steps of: forming a performance fuzzy set for each of the cars, said performance fuzzy set having basis elements corresponding to a plurality of performance criteria and having degrees of membership corresponding to the performance of each of said cars measured in terms of the associated performance criteria; scaling the degrees of membership of terms of each of said performance fuzzy sets by a plurality of values indicative of the assigned importance of each of said performance criteria, thereby forming a plurality of scaled performance fuzzy sets; and forming an assignment utility fuzzy set having basis elements corresponding to the cars of the elevator system and having degrees of membership corresponding to the utility of assigning the associated car wherein each term of said assignment utility fuzzy set equals the term from one of said scaled performance fuzzy sets having the minimum degree of membership.
Claim 21
Dependent Claim
217 words
Method of determining the number of hall passengers waiting for a car at a stop, comprising the steps of: determining a first instantaneous passenger rate in response to a first signal indicating that the car has serviced a stop; determining a second instantaneous passenger rate in response to a second signal indicating that a hall call button has been pressed; scaling said first and second rates by dividing said rates by (i-1)/(F-1), where i is the floor number and F is the total number of building floors, in response to said first and second rates being calculated at a down stop and by dividing said rates by (F-1)/(F-i) in response to said first and second rates being calculated at an up stop; averaging said first and second instantaneous passenger rates into an up-peak, down-peak, or off-peak quantity in proportion to the degrees of membership of terms of a traffic mode fuzzy set having terms indicative of the degree to which the elevator system exhibits up-peak, down-peak and off-peak characteristics; and estimating the number of hall passengers waiting at a particular elevator stop by multiplying the elapsed time since the particular stop was last serviced by said up-peak, down-peak, and off-peak quantities in proportion to the appropriate degrees of membership of terms of said traffic mode fuzzy set.
Claim 22
Dependent Claim
68 words
Method of determining the number of hall passengers waiting for a car at a stop, according to claim 21, wherein determining said first instantaneous passenger rate is comprised of the steps of: subtracting the minimum number of passengers from the final number of passengers to determine the number of boarding passengers; and dividing the number of boarding passengers by the elapsed time since the stop was last serviced.
Claim 23
Dependent Claim
36 words
Method of determining the number of hall passengers waiting for a car at a stop, according to claim 22, wherein the minimum number of passengers and the final number of passengers are expressed as fuzzy sets.
Claim 24
Dependent Claim
28 words
Method of determining the number of hall passengers waiting for a car at a stop, according to claim 22, wherein the number of passengers is a crisp value.
Claim 25
Independent Claim
172 words
A method of determining elevator system traffic mode, comprising the steps of: a first step of setting an up-peak quantity which varies according to the number and frequency of elevator passengers departing from a building lobby; a second step of setting an up-off-peak quantity which varies inversely according to the number and frequency of elevator passengers departing from the building lobby; a third step of setting a down-peak quantity which varies according to the number and frequency of elevator passengers arriving at the building lobby; a fourth step of setting a down-off-peak quantity which varies inversely according to the number and frequency of elevator passengers arriving at the building lobby; a fifth step of setting an off-peak quantity equal to the maximum of said up-off-peak quantity and said down-off-peak quantity; and a sixth step of forming a fuzzy logic set indicative of elevator traffic mode, said set having basis elements corresponding to up, down, and off-peak traffic modes and having respective degrees of membership proportional to said up, down, and off-peak quantities.
Claim 26
Dependent Claim
44 words
A method of determining elevator system traffic mode, according to claim 25, further comprising the step of: defuzzifying said fuzzy logic set to provide a single traffic mode equal to the basis element of said set having the highest degree of membership associated therewith.
Claim 27
Dependent Claim
50 words
A method of determining elevator system traffic mode, according to claim 25, wherein said first step is comprised of the steps of: evaluating a predetermined number of up-peak onset rules; and setting said up-peak quantity to the maximum of the result of evaluating said predetermined number of up-peak onset rules.
Claim 28
Dependent Claim
44 words
A method of determining elevator system traffic mode, according to claim 27, further comprising the step of: defuzzifying said fuzzy logic set to provide a single traffic mode equal to the basis element of said set having the highest degree of membership associated therewith.
Claim 29
Dependent Claim
50 words
A method of determining elevator system traffic mode, according to claim 25, wherein said second step is comprised of the steps of: evaluating a predetermined number of up-off-peak onset rules; and setting said up-off-peak quantity to the maximum of the result of evaluating said predetermined number of up-peak onset rules.
Claim 30
Dependent Claim
44 words
A method of determining elevator system traffic mode, according to claim 29, further comprising the step of: defuzzifying said fuzzy logic set to provide a single traffic mode equal to the basis element of said set having the highest degree of membership associated therewith.
Claim 31
Dependent Claim
50 words
A method of determining elevator system traffic mode, according to claim 29, wherein said third step is comprised of the steps of: evaluating a predetermined number of down-peak onset rules; and setting said down-peak quantity to the maximum of the result of evaluating said predetermined number of down-peak onset rules.
Claim 32
Dependent Claim
44 words
A method of determining elevator system traffic mode, according to claim 31, further comprising the step of: defuzzifying said fuzzy logic set to provide a single traffic mode equal to the basis element of said set having the highest degree of membership associated therewith.
Claim 33
Dependent Claim
50 words
A method of determining elevator system traffic mode, according to claim 25, wherein said fourth step is comprised of the steps of: evaluating a predetermined number of down-off-peak onset rules; and setting said down-off-peak quantity to the maximum of the result of evaluating said predetermined number of down-peak onset rules.
Claim 34
Dependent Claim
44 words
A method of determining elevator system traffic mode, according to claim 33, further comprising the step of: defuzzifying said fuzzy logic set to provide a single traffic mode equal to the basis element of said set having the highest degree of membership associated therewith.
References Cited (Backward Citations)
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