Fuzzy inference circuit using charge coupled device

Details Fuzzy inference circuit using charge coupled device Fuzzy inference circuit using charge coupled device

1997-12-30

2001-04-03

Davis, George B. (Department: 2122)

Data processing: artificial intelligence

Fuzzy logic hardware

Fuzzy inference processing

C706S001000, C706S005000, C706S900000, C706S903000

Reexamination Certificate

active

06212507

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a fuzzy inference circuit, and more particularly, to a fuzzy inference circuit using a charge coupled device.
2. Discussion of the Related Art
A conventional fuzzy inference circuit will be described with reference to the accompanying drawings.
FIG. 1
is a configuration block diagram of a conventional fuzzy inference circuit.
FIG. 2
is a configuration block diagram of a fuzzy rule memory using conventional digital logic.
Referring to
FIG. 1
, a conventional fuzzy inference circuit includes a control object
1
, a sensor
2
, an analog to digital (A/D) converter
3
, a clock generator
4
, a fuzzy rule memory
5
, a fuzzy inference engine
6
, and a digital to analog (D/A) converter
7
.
The sensor
2
senses a state of the control object
1
, and transfers the sensed value of the control object
1
to the A/D converter
3
. The A/D converter
3
converts an analog signal of the sensor
2
to a digital signal.
The fuzzy rule memory
5
stores fuzzy rule function values through digital logic. The fuzzy inference engine
6
receives a clock signal generated from the clock generator
4
in order to perform a fuzzy inference using the fuzzy rule function values and the digitized sensed value in a well-known manner. The D/A converter
7
converts a digital signal from the fuzzy inference engine
6
to an analog signal to control the control object
1
.
Referring to
FIG. 2
, the fuzzy rule memory
5
includes a first memory
8
, a second memory
9
, a comparator
10
, a selector
11
, and a third memory
12
.
The first and second memories
8
and
9
store fuzzy rule function values. The comparator
10
compares the fuzzy rule function values from the first and second memories
8
and
9
with each other to output their comparative value to the selector
11
. The selector
11
selects either the fuzzy rule function value from the first memory
8
or the fuzzy rule function value from the second memory
9
in response to a selective signal S input from the comparator
10
, and transfers the selected value to the third memory
12
. The third memory
12
transfers the fuzzy rule function value transferred from the selector
11
to the fuzzy inference engine
6
.
Referring to
FIG. 1
, fuzzy inference engine
6
receives the clock signal from the clock generator
4
, the digital signal from the A/D converter
3
and the fuzzy rule function values from the fuzzy rule memory
5
, and performs a fuzzy inference on the sensed value using the fuzzy rule function values according to an operational timing established by the clock signal. The fuzzy inferred value from the fuzzy inference engine
6
is converted to an analog value through the D/A converter
7
, and supplied as a control value to the control object
1
.
The conventional fuzzy inference circuit has a problem in that additional memories such as the first, second and third memories are required to store a digital value when the fuzzy inference is performed using a digital circuit. In addition, since an analog signal is input and output, the A/D converter and the D/A converter are additionally required. For this reason, the conventional fuzzy inference circuit has disadvantages such as high cost and slow process speed.
SUMMARY OF THE INVENTION
Accordingly, the present invention is directed to a fuzzy inference circuit using a charge coupled device that substantially obviates one or more of the problems due to limitations and disadvantages of the related art.
An object of the present invention is to provide a fuzzy inference circuit using a charge coupled device in which an area of a memory is reduced and a fast processing speed is achieved.
These and other objects are achieved by providing a fuzzy inference circuit, comprising: a sensor sensing a state of a control object; and a charge coupled device storing fuzzy rule function values for at least one fuzzy rule function, and performing a fuzzy inference on output of said sensor using said fuzzy rule function values to generate a control signal for controlling said control object.
These and other objects are further achieved by providing a fuzzy inference circuit, comprising: a sensor sensing a state of a control object; and a fuzzy rule memory storing fuzzy rule function values for at least one fuzzy rule function using a charge coupled device; a fuzzy inference engine using said charge coupled device to perform a fuzzy inference on output of said sensor based on said fuzzy rule function values; and a defuzzy inference engine generating a control signal for controlling said control object based on output of said fuzzy inference engine.
These and other objects are still further achieved by providing a fuzzy inference method, comprising: sensing a state of a control object using a sensor; storing fuzzy rule function values for at least one fuzzy rule function using a charge coupled device; performing, using said charge coupled device, a fuzzy inference on output of said sensor based on said fuzzy rule function values; and controlling said control object based on output of said performing step.
Other objects, features, and characteristics of the present invention; methods, operation, and functions of the related elements of the structure; combination of parts; and economies of manufacture will become apparent from the following detailed description of the preferred embodiments and accompanying drawings, all of which form a part of this specification, wherein like reference numerals designate corresponding parts in the various figures.


REFERENCES:
patent: 5054040 (1991-10-01), Yariv et al.
patent: 5136685 (1992-08-01), Nagazumi
patent: 5228111 (1993-07-01), Nagazumi
patent: 5247472 (1993-09-01), Nagazumi
“Expert System on a Chip: An Engine for Real-Time Approximate Reasoning,” Togai et al., IEEE, 1986, pps. 55-62.
“A VLSI Fuzzy Logic Controller with Reconfigurable, Cascadable Architecture,” Watanabe et al., IEEE Journal of Solid-State Circuits, vol. 25, No. 2, Apr. 1990, pps. 376-382.
“Neural Networks and Fuzzy Logic, Tools of Promise for Controls,” McCusker, Control Engineering, May 1990, pps. 84-85.

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