JPH04273305A - Power unit - Google Patents

Abstract

PURPOSE:To decide an optimum controlled value with a fuzzy inference by inferring a manipulated value according to a rule decided by a control means and based on the degree where the state value belongs to a prescribed assembly. CONSTITUTION:A CPU 100 serves as an adaptability degree calculation means to calculate the adaptability degree of the detected state value based on the membership function of the state value stored in a ROM 101. Then the CPU 100 serves as an arithmetic means to obtain the inference result of each rule stored in the ROM 101 with a prescribed operation and based on the calculated adaptability degree and also serves as a calculation means to calculate a manipulated value based on the obtained inference result of each rule. In such a way, the CPU 100 performs a fuzzy inference. The ROM 101 serving as a storage means stores the membership function and a fuzzy rule and also a control program. A RAM 102 is used as a work area in the fuzzy inference.

Description

[Detailed description of the invention]

0001

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to power supplies for copying machines, printers, etc.

0002

[Prior Art] Conventionally, as is well known, PWM (Pulse Width Control) using operational amplifiers has been used to control power supplies.
DTH MODULATION) control is used. In this control, the gain of the entire circuit is mainly determined by the gain of the peripheral circuit of the operational amplifier, and this gain determines the rise/fall characteristics of the power supply and the steady state (for example, at constant voltage).
The characteristics of are determined.

0003

[Problems to be Solved by the Invention] However, in the conventional example described above, if the gain of the operational amplifier is low, voltage overshoot occurs when the power supply rises or falls, and as a result, the voltage rises /There was a drawback that the fall time was delayed.

[0004] Furthermore, when the load on a power supply, for example a motor, changes over time, or its torque fluctuates due to a rise in temperature of the motor, the start-up of the power supply changes depending on these fluctuations. The drop characteristics may change, and the optimal voltage that the power supply should supply may change, but
The conventional example cannot cope with this change. That is,
When the number of parameters (state quantities) that determine voltage rise/fall characteristics, optimal voltage, etc. increases, or when there are parameters whose relationship with the control amount is ambiguous, In the conventional example, it is difficult to formulate the relationship between parameters and controlled variables.

[0005] This invention was made to solve the problems of the conventional example as described above. The purpose of the present invention is to provide a power supply device that can determine the optimal control amount by fuzzy inference even when there are various parameters.

[0006]

[Means for Solving the Problems] Therefore, the power supply device according to the present invention achieves the above object by performing fuzzy control, and is configured in detail as follows. (1) a state quantity detection means for detecting a state quantity related to power supply control; a rule means for associating the state quantity with the manipulated variable when performing the power supply control as a qualitative rule;
and inference means for inferring the manipulated variable based on the degree to which the state quantity belongs to a predetermined set according to rules defined by the rule means.

(2) state quantity detection means for detecting a state quantity related to at least one of the control state of the power supply or the load state of the power supply; a state quantity calculation means for calculating a new state quantity from the state quantity; Membership function storage means for storing membership functions each representing a state quantity and an operation quantity in the form of a fuzzy set; a rule storage means for storing a rule expressing the state quantity and the operation quantity in the form of a fuzzy proposition; a fitness calculation means for calculating the fitness of the state quantity detected by the state quantity detection means based on the membership function of the state quantity stored in the membership function storage means; a calculation means for calculating an inference result for each rule stored in the rule storage means by a predetermined calculation based on the degree of conformity; and a calculation means for calculating an operation amount based on the inference result for each rule obtained by the calculation means. , a control means for controlling the operation amount of the power supply control means based on the operation amount calculated by the calculation means.

(3) The state quantity detection means detects, as state quantities, the output voltage of the power supply, the rate of change of the output voltage of the power supply, the room temperature, the humidity, the current of the load of the power supply, and the rate of change of the current of the load of the power supply. Try to detect at least one.

(4) The manipulated variable is the pulse width duty ratio of PWM control or its rate of change.

0010

[Operation] The power supply device according to the present invention configured as described above has a large number of parameters (state quantities), and it is difficult to formulate the relationship between all the parameters and the controlled variable, or the relationship between the parameter and the controlled variable is difficult to formulate. In cases where the relationships are ambiguous, it is possible to determine the control amount by performing fuzzy inference on these ambiguous relationships.

[0011]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Examples of the present invention will be described below in detail with reference to the drawings.

(Structure) FIGS. 1 to 3 show a first embodiment. FIG. 1 is a block diagram showing its configuration. In FIG. 1, 100 is a CPU that (1) serves as a fitness calculation means to calculate the fitness of the detected state quantity based on the membership function of the state quantity stored in the ROM 101, and (2) performs calculations. As a means, an inference result of each rule stored in the ROM 101 is obtained by a predetermined calculation based on the calculated fitness degree, and (3) as a calculation means, an operation amount is calculated based on the obtained inference result of each rule. , which performs fuzzy inference. 100(a) and 100(b) are
A counter and a timer are used to calculate the rate of change in the output voltage of a power supply from a detected state quantity, for example, the output voltage of the power supply.

A ROM 101 serves as a membership function storage means and a fuzzy rule storage means, and stores a control program in addition to fuzzy rules and membership functions. A RAM 102 is used as a work area when performing fuzzy inference. 103 is an interface (I/O) for output signal transfer;
outputs the signal from the driver 106 to the driver 106.

A driver 106 drives the power supply 107 in accordance with the actual operation amount calculated by fuzzy inference. When PWM control is used to control the power supply, the manipulated variable is, for example, a duty ratio. A power supply 107 is controlled based on fuzzy inference, and outputs a voltage to the load 108 in response to a signal from the driver 106. 108 is a load, for example a motor. Reference numeral 109 denotes an output voltage detection circuit as state quantity detection means, which detects the output voltage of the power supply 107. Note that the sensor 109 may use a room temperature sensor or a humidity sensor depending on the case.

Reference numeral 110 denotes a load current detection circuit as state quantity detection means, which detects the value of the current flowing through the load 108. A/D converters 104 and 105 convert analog signals from the output voltage detection circuit 109 and load current detection circuit 110 into digital signals, respectively, and transmit the digital signals to the CPU 100.

(Operation) The operation will be explained based on the above configuration. In the fuzzy control of this example, as a state quantity,
Output voltage of power supply, rate of change of output voltage of power supply, room temperature, humidity, current of load of power supply, rate of change of current of load of power supply, for example, output voltage of power supply (a-1) Change in output voltage of power supply Among the pulse width duty ratio of PWM control and its rate of change, for example, the pulse width duty ratio (c) of PWM control is used as the manipulated variable. The membership functions of those sets are shown in Figure 2. still,
When actually setting the membership function, the difference between the control target voltage and the output voltage (a-1) of the power source is taken, and this is used as the voltage deviation (a).

FIG. 2(a) is the membership function of the voltage deviation, FIG. 2(b) is the membership function of the voltage change rate, and FIG. 2(c) is the voltage control amount, that is, the pulse width duty ratio of PWM control. shows the membership function of Figure 2
As shown in the figure, the sets of voltage deviation, voltage change rate, and pulse width duty ratio of PWM control each have three fuzzy sets.

For example, for three fuzzy sets of voltage deviations, the fuzzy labels are "VL", "VM", and "V
VL (Voltage Low); fuzzy set VM (Voltage Middle) representing "small voltage deviation"; fuzzy set VH (Voltage High) representing "medium voltage deviation"; Let it be a fuzzy set that represents "the deviation is large".

The degree of belonging to each set takes an arbitrary value between "0" and "1", and in the case of a fuzzy set with a fuzzy label VM shown in FIG. 2(a), the voltage deviation is 2V. The degree of belonging to the set, that is, the degree of suitability is "1.
0'', and the degree of adaptation for a voltage deviation of 1.5V or 2.5V is 0.5.

For determining the voltage control amount, that is, the pulse width duty ratio of PWM control, the following fuzzy rules <Rule 5> and <Rule 6> among the fuzzy rules shown in Table 1 are used, for example. <Rule 5> IF (V=VM AND R=RM)
THEN D=DM〈Rule 6〉 IF (V=VM
AND R=RH) THEN D=DL However, V
=Voltage deviation R=Voltage change rate D=Pulse width duty ratio of PWM control.

[0021]

[Table 1]

Next, a method for determining the pulse width duty ratio of PWM control based on <Rule 5>, <Rule 6> and the inference method will be explained. Inferring according to <Rule 6>, for voltage deviation It is included in the RH set with a degree of . Then, take the minimum value of the obtained μX and μY, set the minimum value as the degree to which the condition part of <Rule 6> is satisfied, and combine that value with PW
Take the MIN calculation with the membership function of the pulse width duty ratio of M control. The result of the calculation is a trapezoid shown by the hatched part of the set S shown in FIG.

Next, when inference is made according to <Rule 5>, the calculation result becomes a trapezoid shown by the hatched part of the set T shown in FIG.

Then, the inference results of each rule, that is, the shaded part of the set S and the shaded part of the set T are combined. The synthesis result is the hatched part of the set U shown in FIG. 3, and the center of gravity (point P) of this set is calculated to determine the pulse width duty ratio d of the PWM control.

In this embodiment, fuzzy rules, membership functions, control programs, etc. are stored in the ROM,
Although the calculation is performed using the RAM, a ROM that outputs the manipulated variable corresponding to the input of the state quantity may also be used.

[0026] The state quantity is not limited to voltage deviation or voltage change rate, but any state quantity related to power supply control, such as room temperature, humidity, current of power supply load, rate of change of current of power supply load, etc. It can be used as a state quantity in the invention. Further, the manipulated variable is not limited to the pulse width duty ratio of PWM control, but may also be a rate of change thereof. The number of state quantities is not limited to two,
Any number of combinations are possible.

Note that the above-mentioned fuzzy inference algorithm is just an example, and the algorithm may be modified. For example, instead of taking the center of gravity of the area when combining a plurality of rules, the value on the horizontal axis relative to the maximum value on the vertical axis may be used as the inference result. Furthermore, the number and content of fuzzy rules can be modified based on experience.

Next, a second embodiment of the present invention will be explained. The configuration of the second embodiment is the same as that of the first embodiment, so a description thereof will be omitted. The fuzzy rules of Example 2 are shown in Table 2.

[0029]

[Table 2]

In Table 2, E indicates the load current of the power supply. In addition, EL, EM, and EH are respectively EL; fuzzy set EM representing "the load current of the power supply is small"; fuzzy set EH representing "the current of the power supply load is medium"; This is a fuzzy set representing "large". Optimal PWM control pulse width duty ratio d
The fuzzy inference algorithm for determining is the same as in Example 1, so the details will be omitted.

Next, a third embodiment of the present invention will be described. The configuration of the third embodiment is the same as that of the first embodiment, so a description thereof will be omitted. The fuzzy rules of Example 3 are shown in Table 3.

[0032]

[Table 3]

In Table 3, F represents the rate of change in the current of the power supply load. Also, FL, FM, and FH are each FL;
Fuzzy set FM that represents "the rate of change in the current of the power supply load is small"; Fuzzy set FH that represents "the rate of change of the current of the power supply load is medium";"the rate of change of the current of the power supply load is large" is a fuzzy set representing Optimal PWM control pulse width duty ratio d
The fuzzy inference algorithm for determining is the same as in Example 1, so the details will be omitted.

[0034]

[Effects of the Invention] As described above, according to the present invention, voltage deviation, voltage change rate, room temperature, humidity, power supply load current, power supply load current change rate, and many other ambiguous and mutually related problems can be solved. In the control of power supply devices such as copying machines and printers whose performance is controlled by variable factors (state quantities), the optimum control quantity is calculated from these complexly related state quantities and automatic control is performed. Therefore, the pulse width duty ratio of PWM control can be controlled.

That is, conventionally, power supply control was fixed in response to environmental changes such as room temperature, humidity, power supply load current, rate of change of power supply load current, etc., but as in the present invention, fuzzy control is Accurate control is possible by using inference and controlling by considering complex factors. Furthermore, since the control amount is determined based on a plurality of parameters, even if there is an error in part of the input data, it is possible to prevent a large error from occurring in the control amount.

[Brief explanation of the drawing]

[Figure 1] Configuration diagram of Example 1

[Figure 2] Membership function of Example 1

[Figure 3]
Conceptual diagram of fuzzy inference in Example 1

[Explanation of symbols]

A State quantity detection means B. Regulatory means C Reasoning means

Claims (4)

[Claims] 1. State quantity detection means for detecting a state quantity related to power supply control; rule means for associating the state quantity with a manipulated variable when performing the power supply control as a qualitative rule; and inference means for inferring the manipulated variable based on the degree to which the state quantity belongs to a predetermined set according to rules defined by the rule means. 2. State quantity detection means for detecting a state quantity related to at least one of a control state of a power supply or a load state of a power supply; a state quantity calculation means for calculating a new state quantity from the state quantity; and a state quantity calculation means for calculating a new state quantity from the state quantity; membership function storage means for storing membership functions in which quantities and manipulated variables are each expressed as fuzzy sets; rule storage means for storing rules in which the state quantities and the manipulated quantities are expressed in the form of fuzzy propositions; and the state. a fitness calculation means for calculating the fitness of the state quantity detected by the quantity detection means based on the membership function of the state quantity stored in the membership function storage means; and a fitness calculated by the fitness calculation means. calculation means for calculating the inference result of each rule stored in the rule storage means by a predetermined calculation based on the calculation means; and calculation means for calculating the operation amount based on the inference result of each rule determined by the calculation means; A power supply device comprising: control means for controlling the operation amount of the power supply control means based on the operation amount calculated by the calculation means. 3. The state quantity detection means detects at least one of the output voltage of the power supply, the rate of change of the output voltage of the power supply, the room temperature, the humidity, the current of the load of the power supply, and the rate of change of the current of the load of the power supply, as the state quantity. 3. The power supply device according to claim 1, wherein the power supply device detects one of the two. 4. The power supply device according to claim 1, wherein the manipulated variable is a pulse width duty ratio of PWM control or a rate of change thereof.