JP2557722B2 - Absorption refrigerator control method - Google Patents

Description

TECHNICAL FIELD The present invention relates to an absorption refrigerator, and more particularly to a method of controlling the absorption refrigerator.

(B) Prior art In Japanese Patent Laid-Open No. 58-160778, for example, the cold water outlet temperature is detected to control the amount of heat to the regenerator, and the level of the absorbing liquid in the regenerator is detected to detect the absorber. Control the amount of rare absorbent flowing from the regenerator to the regenerator, and detect the cold water inlet temperature to determine the appropriate value of either the heating amount of the regenerator for this temperature or the amount of rare absorbent flowing to the regenerator. There is disclosed a control device for an absorption refrigerating machine which controls one of the heating amount and the amount of the rare absorption liquid based on this value.

(C) Problem to be Solved by the Invention In the above-mentioned conventional technique, proportional control or PID control for detecting the cold water outlet temperature to control the heating amount of the regenerator is general.

However, the above-mentioned control has a problem in that it has poor responsiveness to start-up, stop, gradual load fluctuation, sudden load fluctuation, or cooling water temperature fluctuation.

It is an object of the present invention to provide a control device for an absorption refrigerating machine, which has good responsiveness to start-up, stop, load fluctuation and the like.

(D) Means for Solving the Problems In order to solve the above problems, the present invention is based on the deviation from the set value of the cold water outlet temperature from the evaporator (4), the membership function, and the fuzzy rule. The present invention provides a control method for an absorption refrigerator that controls the heating amount of a high temperature generator (1) by fuzzy logic operation.

Further, the high temperature generator (1) is heated by the fuzzy logic operation based on the deviation from the set value of the cold water outlet temperature from the evaporator (4), the rate of change of the cold water outlet temperature, the membership function and the fuzzy rule. It is intended to provide a control method of an absorption refrigerator for controlling the amount.

In addition, the deviation from the set value of the cold water outlet temperature from the evaporator (4), the rate of change of the cold water outlet temperature, the rate of change of the cold water inlet temperature to the evaporator (4), the membership function and the fuzzy rule Based on this, a method for controlling an absorption refrigerator is provided which controls the heating amount of a high temperature generator (1) by fuzzy logic operation.

Further, the deviation from the set value of the cold water outlet temperature from the evaporator (4), the change rate of the cold water outlet temperature, the change rate of the cold water inlet temperature to the evaporator (4), the change rate of the cooling water inlet temperature, and the member The present invention provides a control method for an absorption refrigerator that controls the heating amount of a high temperature generator (1) by fuzzy logic operation based on a ship function and a fuzzy rule.

(E) Action During operation of the absorption refrigerator, the cold water outlet temperature, the cold water inlet temperature,
Or, when the cooling water inlet temperature is detected, the fuzzy logic operation is performed by the fuzzy inference processor (27) based on the deviation from the set value or the rate of change of temperature, the membership function and the fuzzy rule, Fuel control valve (17)
Is required. Therefore, the fuel control valve (17)
The opening degree can be controlled by a control rule based on human experience, and it is possible to provide an absorption refrigerating machine with good responsiveness to load fluctuations and the like.

(F) Embodiment Hereinafter, a first embodiment of the present invention will be described in detail with reference to the drawings.

Figure 1 shows a dual-effect absorption refrigerator that uses water as the refrigerant and lithium bromide (LiBr) solution as the absorbent (solution).
(1) is a high temperature generator equipped with a burner (IB), (2) is a low temperature generator, (3) is a condenser, (4) is an evaporator, (5)
Is an absorber, (6) is an absorbent pump, (7) and (8) are a low temperature heat exchanger and a high temperature heat exchanger, respectively, (10) is a rare absorbent pipe, (11) is an intermediate absorbent pipe, ( 12) concentrated absorbent pipe, (13) refrigerant pipe, (14) refrigerant liquid down pipe, (15)
Are refrigerant liquid circulation pipes, which are connected as shown in FIG. A refrigerant pump (15P) is provided in the refrigerant circulation pipe (15). Further, (16) is a fuel supply pipe connected to the burner (1B), and a fuel control valve (17) is provided in the middle of the fuel supply pipe (16). Further, (20) is a cold water pipe, and this cold water pipe (20)
An evaporator heat exchanger (21) is provided midway. Further, (22) is a cooling water pipe.

Reference numeral (23) is a microcomputer control panel of the absorption refrigerator, and (24) is a cold water outlet temperature detector provided in the cold water pipe (20). The cold water outlet temperature detector (24) and the fuel control valve (17) And the microcomputer control panel (23) are connected. The microcomputer control panel (23) is provided with a microprocessor (25) for executing fuzzy inference based on the cold water outlet temperature and the like, and a control device (26) for the fuel control valve (17). The microprocessor (25) is composed of a fuzzy inference processor (arithmetic device) (27) and a control rule storage device (28). The fuzzy inference processor (27) logically calculates the opening of the fuel control valve (17), that is, the operation amount, using the deviation from the set value of the chilled water outlet temperature, and outputs the obtained operation amount to the control device (26). . The control device (26) controls the opening degree of the fuel control valve (17) based on the operation amount. In this embodiment, the opening degree of the fuel control valve (17) is output from the fuzzy inference processor (27). The control rule storage device (28) is a fuzzy inference processor (27).
The control rules and the membership functions required for the fuzzy logic operation executed in step S1 are stored. Further, (30) is an arithmetic unit, and the arithmetic unit (30) is a chilled water outlet temperature detector (2
4) Input the temperature data and calculate the deviation from the set value.

The fuzzy logic operation for obtaining the opening of the fuel control valve (17) is executed based on the following control rule and membership function. The control rules (fuzzy rules) stored in the storage device (28) will be described below based on human experience.

R ₁ : If the chilled water outlet temperature is considerably higher than the set value (eg, 7 ° C), that is, the deviation of the chilled water outlet temperature from the set value (eT
If o) is PB (Positive Big), open the fuel control valve (17) immediately (PB).

R _2: If the cold water outlet temperature is slightly higher than the set value, i.e. the deviation (ETO) is PS (Positive Small: positive small), then the fuel control valve (17) gradually opens (PS).

R _3: If the cold water outlet temperature is equal to the set value, i.e. the deviation (ETO) is ZR (Zero: zero), then maintaining the opening degree of the fuel control valve (17) intact (ZR).

R ₄ : If the cold water outlet temperature is slightly lower than the set value, that is, if the deviation (eTo) is NS (Negative Small), gradually close the fuel control valve (17) (NS).

R ₅ : If the chilled water outlet temperature is considerably lower than the set value, that is, if the deviation (eTo) is NB (Negative Big), the fuel control valve (17) is immediately closed (NB).

The above R _{1 to} R ₅ are control rules, and this control rule is as shown in FIG. In FIG. 3, KQ is the manipulated variable of the fuel control valve (17).

Further, among the membership functions, the membership function for qualitatively evaluating the magnitude of the deviation from the set value of the cold water outlet temperature, that is, the fuzzy variables PB, PS, ZR, NS, and NB for the above deviation The membership function is defined as shown in FIG.

In addition, a membership function for converting the manipulated variable of the fuel control valve (17) qualitatively evaluated into a quantitative value, that is, the fuzzy variable PB for the manipulated variable (opening) of the fuel control valve (17). , PS, ZR, NS, NB membership functions are defined as shown in FIG.

Then, the fuzzy logic operation is performed in the fuzzy inference processor (27) using the control rule shown in FIG. 3 and the membership function shown in FIGS. 2 and 4,
The operation amount of the fuel control valve (17) is obtained.

The operation of the absorption refrigerator will be described below. During operation of the absorption refrigerator, the burner (1B) burns and the absorption liquid pump (6) and the refrigerant pump (15P) are operated, so that the absorption liquid and the refrigerant circulate as in the conventional absorption refrigerator. Then, the refrigerant liquid is sprayed to the evaporator heat exchanger (21) in the evaporator (4), and the cold water whose temperature has been lowered in the evaporator heat exchanger (21) is supplied to the load.

The control of the heating amount of the high temperature generator (1) when the absorption refrigerator is operated as described above will be described.

During the operation of the absorption refrigerator, the cold water outlet temperature detector (24) detects the temperature of the cold water from the evaporator (4). Then, the temperature data of the cold water is given to the fuzzy inference processor (27) of the control panel (23). The fuzzy inference processor (27) calculates the membership value at the chilled water outlet temperature using the membership function of the fuzzy variable with respect to the temperature stored in advance in the storage device (28). And this membership value becomes the above control rule (R ₁ ~
Antecedent of R _5), i.e. (R ₁₎ in the cold water outlet temperature is calculated the ratio meets that considerably higher than the set value in fuzzy logic product. And the above control rule (R _{1 to} R ₅ )
The ratio of the antecedent part for each of the fuzzy variables (PB, PS, Z
R, NS, NB) Membership function
Modify the ship function.

Next, by the membership function of the modified control rule, the manipulated variable of the fuel control valve (17) according to the deviation from the set value of the chilled water outlet temperature, that is, the fuel control valve (1
The optimum opening of 7) is required.

Here, when the deviation of the chilled water outlet temperature is, for example, −0.6 ° C., the membership value (A) is obtained by the membership function and the control rule as shown in FIG.
From the center of gravity (g) of the membership value (A), the operation amount (control valve opening) of the fuel control valve (17) can be obtained. Then, this manipulated variable is output to the control device (26), the opening signal output from the control device (26) changes, and the opening of the fuel control valve (17) is maintained at the optimum opening.

According to the above embodiment, the human experience of controlling the fuel control valve (17) corresponding to the deviation from the set value of the chilled water outlet temperature is stored in the storage device (28) as a control rule, and the membership The opening of the fuel control valve (17) can be adjusted based on human experience by calculating the function, and the heating amount of the high temperature generator (1) can be controlled according to the deviation from the set value of the cold water outlet temperature. As a result, the coefficient of performance of the absorption refrigerator can be improved.

A second embodiment of the present invention will be described below in which the manipulated variable of the fuel control valve (17) is fuzzy inferred using the deviation from the set value of the cold water outlet temperature and the rate of change of the cold water outlet temperature.
In addition to the control rules of the first embodiment, the storage device (28) stores the following control rules for the rate of change of the chilled water outlet temperature and a membership function based on human experience.

R ₁ : If the cold water outlet temperature rises rapidly, that is, if the rate of change (dTo) of the cold water outlet temperature is PB, the fuel control valve (17) is immediately opened (PB).

R ₂ : If the chilled water outlet temperature rises slightly, that is, if the rate of change is PS, gradually open the fuel control valve (17) (PS).

R ₃ : No change in cold water outlet temperature, that is, if the rate of change is ZR,
Maintain fuel control valve (17) at present (ZR).

R ₄ : If the chilled water outlet temperature is slightly lowered, that is, if the rate of change is NS, gradually close (NS) the fuel control valve (17).

R ₅ : If the cold water outlet temperature drops sharply, that is, the rate of change is NB
Then, open the fuel control valve (17) immediately (NB).

The control rules for R _{1 to} R ₅ are as shown in FIG.

In addition, the fuzzy variables PB, P for the rate of change of the cold water outlet temperature
The membership functions of S, ZR, NS and NB are shown in FIG. The membership function of the fuzzy variables PB, PS, ZR, NS, NB with respect to the opening of the fuel control valve (17) is shown in FIG.

Then, a fuzzy logic operation is performed by the fuzzy inference processor (27) using the control rule shown in FIG. 6 and the membership function shown in FIGS. To be

As described above, the control rule and membership function for the rate of change of the cold water outlet temperature and the control rule and membership function for the deviation of the cold water outlet temperature from the set value are stored in the storage device (28). In addition to the deviation, the arithmetic unit (30) also calculates the rate of change (change in chilled water outlet temperature for 1 minute) (° C./min) based on the chilled water outlet temperature. Then, when the absorption chiller is operating, the fuzzy logic operation is performed by the fuzzy inference processor (27) by the control rule and the membership function based on the deviation from the set value of the chilled water outlet temperature as in the first embodiment. Then, the membership value of the manipulated variable of the fuel control valve (17) corresponding to the above deviation is obtained. Here, when the deviation is −0.6 ° C., the membership value is (A) in FIG. 14 as in the first embodiment. Further, based on the change rate of the chilled water outlet temperature, fuzzy logic operation is performed by the fuzzy inference processor (27) by the control rule shown in FIG. 6 and the membership function shown in FIGS. 5 and 7, The membership value of the manipulated variable of the fuel control valve (17) corresponding to the rate of change is obtained. Here, when the rate of change is −0.8 ° C./min, the membership value (B) is obtained as shown in FIG. Then, the fuzzy inference processor (27) obtains the logical sum of the membership values (A) and (B) of the respective manipulated variables, and the manipulated variable is determined from the center of gravity of this logical sum, and outputs it to the control device (26). To be done. An opening signal is output from the control device (26) to the fuel control valve (17) based on the manipulated variable, and the valve opening is maintained at the optimum opening.

According to the second embodiment described above, the human experience in controlling the fuel control valve (17) corresponding to the deviation from the set value of the cold water outlet temperature and the rate of change is stored as a control rule in the storage device (2
It can be stored in 8) and the degree of opening of the fuel control valve (17) can be calculated based on human experience by fuzzy reasoning, and even when the load changes and the chilled water outlet temperature changes,
The heating amount of the high temperature generator (1) can be adjusted according to the change, and as a result, the cold water outlet temperature can be further stabilized.

A third embodiment of the present invention in which the manipulated variable of the fuel control valve (17) is fuzzy inferred using the deviation from the set value of the cold water outlet temperature, the rate of change of the cold water outlet temperature, and the rate of change of the cold water inlet temperature. Will be described. (31) is a cold water inlet temperature detector attached to the inlet side cold water pipe (20) of the evaporator (4), and this temperature detector (31) is detected by the arithmetic unit (30) of the control panel (23). Output the temperature data. In addition to the control rules of the storage device (28) or the first and second embodiments,
Control rules and membership functions for the rate of change of cold water inlet temperature are stored based on human experience.

Hereinafter, the control rule and the membership function for the rate of change of the cold water inlet temperature will be described. The control rules are R _{1 to} R ₅ below, which are shown in FIG.

R ₁ : If the cold water inlet temperature rises rapidly, that is, if the rate of change of the cold water inlet temperature (dTi) is PB, open the fuel control valve (17) immediately (PB).

R _2: If the cold water inlet temperature is slightly raised, i.e., the rate of change if the PS, the fuel control valve (17) gradually opens (PS).

R _3: cold water if the inlet temperature of no change, i.e., if the rate of change ZR, maintain fuel control valve (17) at present (ZR).

R ₄ : If the cold water inlet temperature is slightly lower, that is, if the rate of change is NS, gradually close (NS) the fuel control valve (17).

R ₅ : If the cold water inlet temperature drops sharply, that is, the rate of change is NB
Then close the fuel control valve (17) immediately (NB).

Also, a fuzzy variable for the rate of change of the cold water inlet temperature
Membership functions of PB, PS, ZR, NS and NB are shown in FIG. Also, the membership function of the fuzzy variables PB, PS, ZR, NS, NB for the opening of the fuel control valve (17) is
It is shown in Fig. 10.

Then, the control rule shown in FIG.
Fuzzy logic operation is performed in the fuzzy inference processor (27) using the membership function shown in Fig. 10,
The manipulated variable is required.

As described above, the control rule and the membership function for the deviation from the set value of the cold water outlet temperature, the rate of change of the cold water outlet temperature, and the rate of change of the cold water inlet temperature are stored in the storage device (28). . The arithmetic unit (30) also calculates the rate of change of the cold water inlet temperature based on the cold water inlet temperature.

During operation of the absorption chiller, similar to the second embodiment, the fuzzy inference processor (27) is controlled by the control rule and the membership function based on the deviation from the set value of the cold water outlet temperature and the rate of change of the cold water outlet temperature. Fuzzy logic operation is performed at. Then, the membership value of the manipulated variable of the fuel control valve (17) is obtained in accordance with the deviation and the rate of change. Further, a fuzzy logic operation is performed by a fuzzy inference processor (27) using the control rule shown in FIG. 9 and the membership function shown in FIGS. 8 and 10 based on the rate of change of the cold water inlet temperature. Then, the membership value of the manipulated variable of the fuel control valve (17) corresponding to the above change rate is obtained. Then, for example, in the case of the MAX centroid calculation method, the fuzzy inference processor (24) uses a deviation from the set value of the cold water outlet temperature, a change rate of the cold water outlet temperature, and a fuel control valve (17) based on the change rate of the cold water inlet temperature. ), The logical sum of each membership value of the operation amount is obtained, and the operation amount is obtained from the center of gravity. Then, this operation amount is controlled by the control device (2
It is output to 6). An opening signal is output from the control device (26) to the fuel control valve (17) based on the manipulated variable, and the valve opening is maintained at the optimum opening corresponding to the rate of change of the cold water inlet temperature.

According to the third embodiment described above, in addition to the deviation of the chilled water outlet temperature from the set value and the rate of change of the chilled water outlet temperature, human control of the fuel control valve (17) corresponding to the rate of change of the chilled water inlet temperature is performed. Experience is stored as a control rule in the storage device (28), and when the cold water inlet temperature changes, the opening of the fuel control valve (17) can be adjusted based on human experience by calculating the membership function. When the load changes and the cold water inlet temperature changes, the heating amount of the high temperature generating part (1) can be adjusted according to the change, and the cold water outlet temperature is more stable regardless of the load change. Can be made.

The fuel control valve (17) will be described below using the deviation from the set value of the cold water outlet temperature, the change rate of the cold water outlet temperature, the change rate of the cold water inlet temperature, and the change rate of the cooling water inlet temperature to the absorber (5). A fourth embodiment of the present invention for fuzzy inferring the operation amount of will be described. Reference numeral (32) is a cooling water inlet temperature detector attached to the cooling water pipe (22) on the inlet side of the absorber (5), and this temperature detector (32) calculates temperature data from an arithmetic unit (3
Output to 0). The arithmetic unit (30) calculates the rate of change of the cooling water inlet temperature based on the deviation from the set value of the cold water outlet temperature, the rate of change of the cold water outlet temperature and the temperature of the cold water inlet, and the inputted temperature data. Further, the storage device (28) has the above first and second
In addition to the control rules and membership functions of the second and third embodiments, a control rule for the temporal change of the cooling water inlet temperature, that is, a rate of change of the cooling water inlet temperature based on human experience, and The membership function is stored.

Hereinafter, the control rule and the membership function for the rate of change of the cooling water inlet temperature will be described. The control rules are R _{1 to} R ₅ below, which are shown in FIG.

R ₁ : If the cooling water inlet temperature rises rapidly, that is, if the rate of change (dTci) of the cooling water inlet temperature is PB, the fuel control valve (17) is immediately opened (PB).

R ₂ : If the cooling water inlet temperature rises slightly, that is, the rate of change is PS
Then, gradually open the fuel control valve (17) (PS).

R ₃ : If there is no change in the cooling water inlet temperature, that is, the rate of change is ZR
Then, keep the fuel control valve (17) as it is (ZR).

R _4: If the cooling water inlet temperature is slightly lowered, i.e. the rate of change NS
Then, gradually close (NS) the fuel control valve (17).

R ₅ : If the cooling water inlet temperature drops sharply, that is, the rate of change is
If it is NB, open the fuel control valve (17) immediately (NB).

Further, the membership function of the fuzzy variables PB, PS, ZR, NS and NB with respect to the rate of change of the cooling water inlet temperature is shown in FIG. The membership function of the fuzzy variables PB, PS, ZR, NS, NB with respect to the opening of the fuel control valve (17) is shown in FIG.

Then, the control rule shown in FIG.
A fuzzy logic operation is performed in the fuzzy inference processor (27) using the membership function shown in FIG.
The manipulated variable is required.

As described above, in addition to the control rule and the membership function shown in the third embodiment, the storage device (28) stores the control rule and the membership function of the rate of change of the cooling water inlet temperature. .

During operation of the absorption chiller, similar to the third embodiment, each control rule and membership function are based on the deviation from the set value of the cold water outlet temperature, the change rate of the cold water outlet temperature and the cold water inlet temperature. The fuzzy inference processor (27) performs a fuzzy inference operation by a member of the manipulated variable of the fuel control valve (17) according to the above deviation and each change rate.
Ship value is calculated respectively. Here, when the deviation from the set value of the cold water outlet temperature is, for example, −0.6 ° C., the 14th
As shown in the figure, fuzzy inference is performed, and the membership value of the manipulated variable of the fuel control valve (17) due to the above deviation becomes as shown in (A). When the rate of change of the cold water outlet temperature is, for example, −0.8 ° C./min, fuzzy reasoning is performed as shown in FIG. 15, and the fuel control valve (17) based on the rate of change is
The membership value of the operation amount of is as shown in (B).
Furthermore, when the rate of change of the cold water inlet temperature is 0.4 ° C / min, for example, fuzzy inference is performed as shown in Fig. 16,
The membership value of the manipulated variable of the fuel control valve (17) according to the above change rate is as shown in (C).

In addition, fuzzy inference processor (27) performs fuzzy inference calculation using control rules and membership functions based on the rate of change of cooling water inlet temperature, and controls fuel according to the rate of change of cooling water inlet temperature. The manipulated variable of the valve (17) is required. Here, the rate of change of the cooling water inlet temperature is, for example, −0.5.
At ℃ / min, fuel control valve (17) with the above rate of change
The membership value of the manipulated variable is calculated by fuzzy reasoning.
It becomes like (D) in Figure 17. And, for example, in the case of the MAX centroid calculation method, the membership values (A), (B) of the manipulated variable of the fuel control valve (17) by the above deviation and each change rate are
The logical sum of (C) and (D) is calculated. This logical sum is the outline (E) of FIG. 18 when the membership values (A), (B), (C), and (D) are overlapped, and the center of gravity of the logical sum (E) ( G) Determine the manipulated variable of the fuel control valve (17).

The operation amount obtained as described above is output to the control device (26), the control device (26) outputs an opening signal to the fuel control valve (17) based on the operation amount, and the valve opening is cooled. The optimum opening is maintained according to the rate of change of the water inlet temperature.

According to the fourth embodiment, in addition to the deviation from the set value of the cold water outlet temperature, the rate of change of the cold water outlet temperature and the cold water inlet temperature, the control of the fuel control valve corresponding to the rate of change of the cooling water inlet temperature is performed. Human experience is stored as a control rule in the storage device (28), and when the cooling water inlet temperature changes, the degree of opening of the fuel control valve (17) is adjusted by fuzzy inference calculation based on human experience. Therefore, the heating amount of the high temperature generator (1) can be adjusted according to the change, and the cold water can be stably supplied to the load regardless of the temperature change of the cooling water.

In addition, in the fourth embodiment, fuzzy inference is performed based on the deviation from the set value of the cold water outlet temperature and the rate of change of the cold water outlet temperature, the cold water inlet temperature and the cooling water inlet temperature of the fuel control valve (17). The opening was adjusted, but the deviation and the change rate of the cold water inlet temperature, or the deviation and the change rate of the cooling water inlet temperature, or the deviation and the change rate of the cold water outlet temperature and the cooling water inlet temperature, or the deviation and the cold water. Fuzzy inference may be performed based on the change rates of the inlet temperature and the cooling water inlet temperature to obtain the operation amount of the fuel control valve, and the opening degree of the fuel control valve (17) may be adjusted.

(G) Effect of the Invention The present invention is a method for controlling an absorption refrigerator as described above,
Generated by fuzzy logic operation based on deviation from chilled water outlet temperature set value, chilled water outlet temperature change rate, chilled water inlet temperature change rate, or chilled water inlet temperature change rate, membership function and fuzzy rule Since the heating amount of the vessel is controlled, it is possible to change the load or the cooling water temperature.
When the chilled water outlet temperature, chilled water inlet temperature, or chilled water inlet temperature changes, it is possible to control the heating amount of the generator based on human experience, and it is generated according to the load change or the chilled water temperature. It is possible to stabilize the temperature of cold water or hot water by adjusting the heating amount of the vessel.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a circuit configuration diagram of an absorption chiller showing an embodiment of the present invention, and FIG. 2 is a diagram showing a membership function of a fuzzy variable with respect to a deviation from a set value of a chilled water outlet temperature. , FIG. 3 is a diagram showing a control rule between the deviation and the manipulated variable, and FIGS. 4, 7, 10, and 13 show the membership function of the fuzzy variable with respect to the control valve opening, respectively. Fig. 5, Fig. 5 is a diagram showing a membership function of a fuzzy variable with respect to the change rate of cold water outlet temperature, Fig. 6 is a view showing a control rule between the change rate and the manipulated variable, and Fig. 8 is cold water. Member of fuzzy variable for rate of change of inlet temperature
FIG. 9 is a diagram showing a ship function, FIG. 9 is a diagram showing a control rule between the change rate and the manipulated variable, and FIG. 11 is a diagram showing a fuzzy variable membership function with respect to the change rate of the cooling water inlet temperature. Fig. 12 is a diagram showing a control rule between the rate of change and the manipulated variable, Fig. 14 is an explanatory diagram of fuzzy reasoning when the deviation from the set value of the cold water outlet temperature is -0.6 ° C, and Fig. 15 is the cold water. Fig. 16 is an explanatory diagram of fuzzy reasoning when the outlet temperature is -0.8 ° C / min, Fig. 16 is an explanatory diagram of fuzzy reasoning when the rate of change of the cold water inlet temperature is 0.4 ° C / min, and Fig. 17 is the cooling water inlet temperature. Explanatory diagram of fuzzy reasoning when the rate of change is -0.5 ° C / min,
Fig. 18 shows the manipulated variable of the fuel control valve by the MAX centroid calculation method from the deviation from the set value of the cold water outlet temperature, the change rate of the cold water outlet temperature, the change rate of the cold water inlet temperature, and the change rate of the cooling water inlet temperature. It is explanatory drawing of a case. (1) ... High temperature generator, (3) ... Condenser, (4) ... Evaporator, (5) ... Absorber, (24) ... Cold water outlet temperature detector,
(28) ... Memory device, (27) ... Fuzzy inference processor (arithmetic unit).

Front page continued (72) Inventor Masahiro Furukawa 2-18 Keihan Hondori, Moriguchi City, Osaka Sanyo Electric Co., Ltd. (72) Inventor Toshiyuki Kaneko 2-18 Keihan Hondori, Moriguchi City, Osaka Sanyo Electric Co., Ltd. In-house (56) Reference JP 63-251764 (JP, A) JP 58-160778 (JP, A) JP 63-131942 (JP, A)

Claims (4)

(57) [Claims] 1. A method of controlling an absorption chiller, wherein an evaporator, an absorber, a generator, a condenser, etc. are connected to form a refrigeration cycle, and a heating amount of the generator is controlled, wherein a cold water outlet from the evaporator. A method for controlling an absorption refrigerator, wherein the heating amount of the generator is controlled by a fuzzy logic operation based on a deviation from a set value of temperature, a membership function and a fuzzy rule. 2. A cooling water outlet from an evaporator in a method for controlling an absorption refrigerator in which a refrigeration cycle is formed by connecting an evaporator, an absorber, a generator, a condenser and the like, and the heating amount of the generator is controlled. It is characterized in that the heating amount of the generator is controlled by a fuzzy logic operation based on the deviation from the set value of the temperature, the change rate of the cold water outlet temperature, the membership function and the fuzzy rule. Control method of absorption refrigerator. 3. A method of controlling an absorption chiller, wherein an evaporator, an absorber, a generator, a condenser, etc. are connected to form a refrigeration cycle and a heating amount of the generator is controlled, and a cold water outlet from the evaporator. The heating amount of the generator is controlled by a fuzzy logic operation based on the deviation from the set temperature, the change rate of the cold water outlet temperature, the change rate of the cold water inlet temperature to the evaporator, the membership function and the fuzzy rule. A method for controlling an absorption refrigerator, the method comprising: 4. A method for controlling an absorption chiller in which an evaporator, an absorber, a generator, a condenser, etc. are connected to form a refrigeration cycle and the heating amount of the generator is controlled, wherein cold water outlet from the evaporator is used. Deviation from temperature setting, change rate of cold water outlet temperature, change rate of cold water inlet temperature to evaporator, change rate of cooling water inlet temperature to absorber, membership function and fuzzy
A method for controlling an absorption chiller, characterized in that the heating amount of the generator is controlled by fuzzy logic operation based on rules.