Boots – shoes – and leggings
Patent
1990-11-23
1993-08-31
Fleming, Michael R.
Boots, shoes, and leggings
364149, 395900, 395906, G05B 1302
Patent
active
052416518
DESCRIPTION:
BRIEF SUMMARY
TECHNICAL FIELD
This invention relates to an operating method in a fuzzy control apparatus and to an adjusting device thereof. More particularly, the invention relates to a method of operating a fuzzy control apparatus and to a device for adjusting the apparatus, wherein the fuzzy control apparatus presets plural types of membership functions with regard to respective ones of at least one type of input, which is derived based on a controlled variable obtained from a controlled system, and an output relating to a manipulated variable applied to the controlled system, and derives the output by performing a fuzzy inferential operation in accordance with predetermined control rules using the input and several of the set membership functions.
BACKGROUND ART
By employing a skilled operator's experience and intuition in the form of rules, a fuzzy control apparatus seeks to control a process that cannot be controlled well by a conventional PID control apparatus.
A fuzzy control apparatus is based on fuzzy theory. Fuzzy theory seeks to realize artificial intelligence and robotics by formalizing sophisticated human thought and quantitative methods of judgment and then incorporating these in a computer.
FIG. 1 illustrates a control system using a fuzzy control apparatus. A fuzzy control apparatus 10 calculates a manipulated-variable output U based on an error e between a controlled variable Y, which is obtained from a controlled system (process) 20, and a prescribed set value (target value) SV, and a rate of change .DELTA.e in the error (in case of control based on sampled values, the difference between an error e.sub.n of a present sampling and an error e.sub.n-1 of the immediately preceding sampling). The output U is supplied to the controlled system 20.
Using membership functions relating to errors and rates of change thereof defined beforehand in rules, the fuzzy control apparatus 10 judges the conformity of the error e and rate of change .DELTA.e thereof to the rules. In accordance with the degree of conformity, the apparatus obtains inferential results based on membership functions relating to a manipulated variable similarly defined for every rule, computes the center of gravity of these inferential results and outputs the center of gravity as a manipulated variable.
FIG. 2 illustrates a table in which is set a change .DELTA.U in a manipulated variable in rules created for each important combination of an error and the rate of change thereof. NL represents a negative large value, NM a negative medium value, NS a negative small value, ZR almost zero, PS a positive small value, PM a positive medium value, and PL a positive large value. For example, if e=NS and .DELTA.e=PS, namely if the controlled variable is a little smaller than the target value and is rising a little, then .DELTA.U is decided in such a manner that .DELTA.U=ZR will hold, i.e., in such a manner that the manipulated variable will not change. In each rule, the error e, the rate of change .DELTA.e of the error and the rate of change .DELTA.U of the manipulated variable are evaluated using membership functions defined in advance.
FIGS. 3a through 3c illustrate examples of membership functions related to the error e. FIG. 3a illustrates the shape common to PM, PS, ZR, NS and NM. The membership functions are isosceles triangles about a central value .alpha., in which the length of the base is l and the height (grade) of the apex is 1. The position of the central value .alpha. differs in dependence upon the type PM, PS . . . of membership function. FIG. 3b shows the membership function in the case of PL. In the region e<K.sub.1, the shape is the same as in FIG. 3a, and the grade is 1 at e.gtoreq.K.sub.1. FIG. 3c shows the membership function in case of NL. In the region e>-K.sub.1, the shape is the same as in FIG. 3a, and the grade is 1 at e.ltoreq.-K.sub.1.
Membership functions relating to the rate of change .DELTA.e in the error and the rate of change .DELTA.U in the manipulated variable are also of the same shapes as the membership functi
REFERENCES:
patent: 4646226 (1987-02-01), Moon
patent: 5038269 (1991-08-01), Grimble et al.
Larsen, P. M., "Industrial Applications of Fuzzy Logic Control", Intl. J. Man-Machine Studies, 1980, 3-10.
Sarture et al., "Performance Criteria in Adaptive Control", in Adaptive Control Systems, The Macmillan Co., 1963, 1-10.
Downs Robert W.
Fleming Michael R.
Omron Corporation
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