JP3268662B2 - Image processing device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus such as a copying machine or a printer, and more particularly to an image processing apparatus which performs control by applying fuzzy inference.

[0002]

2. Description of the Related Art In a copying machine, a printer or the like, there is a change in an electrostatic latent image as a major factor in a change in image quality. This change in the electrostatic latent image is caused by a change in the drum sensitivity, a change in the discharge amount of the primary charger, and a change in the exposure amount. These changes are caused by the installation environment of the machine (for example, temperature, humidity, etc.) and related components. It is caused by deterioration, dirt, etc. Therefore, even if these factors occur, there is a drum surface potential control mechanism in order to obtain an electrostatic latent image as stable as possible.

Conventionally, this drum surface potential control mechanism changes only the bright portion target potential (VL), the dark portion target potential (VD), and the control coefficient in accordance with the drum sensitivity so that an appropriate image can be obtained. It has the following configuration. That is, when measuring the dark area potential , a reference current is applied to the primary charger, and the potential sensor measures the drum surface potential. And, based on the measured value, DC
The measured value of the drum surface potential is compared with the target value on the controller board, and if the drum surface potential is out of the target value,
The primary charge level control signal output from the DC controller board is corrected. Thereby, the corrected current is applied to the primary charger from the high-voltage transformer.

The above measurement and correction are repeated three times to bring the dark portion potential closer to the target value. When measuring the bright portion target potential , the reference lighting voltage is applied to the original illumination lamp. The document illumination lamp illuminates a standard white plate and projects the reflected light onto a drum. Then, the drum surface potential of the portion projected on the drum is measured by a potential sensor and input to the DC controller board. This DC controller board compares the measured value with the target value. If the measured value is out of the target value,
The light amount adjustment signal output from the DC controller board is corrected. As a result, the corrected voltage is applied from the lamp regulator to the original illumination lamp.

[0005] The above measurement and correction are repeated three times to bring the light portion potential closer to the target value. Note that the above-described operation is not performed for each copy, but is performed at certain time intervals. Further, the light portion target potential, the dark portion target potential, and the control coefficient are set according to the sheet contained in the drum, and this setting is performed only when the drum is replaced. Further, in PWM (pulse width modulation) control using an operational amplifier, which has been conventionally used for controlling the potential, the gain of the entire control circuit is mainly determined by the gain of the peripheral circuit of the operational amplifier, and the rise of the potential at this gain. , Falling characteristics and steady-state characteristics (for example,
In the case of constant voltage control, voltage regulation) is determined.

This voltage control cannot cope with a change in the rise / fall characteristics of the potential due to, for example, a change in potential load due to a change over time in the motor or a change in torque for raising the temperature of the motor. The rising / falling characteristic of the potential and the characteristic in a steady state are controlled using inference control. The reason for the inability to cope with the change in the characteristics is that the number of parameters that determine the rise / fall characteristics of the potential increases, or that there is a parameter whose relationship with the control amount is ambiguous among the parameters. This is because it is difficult to formulate the relationship between the parameter and the control amount.

By the way, conventionally, in an image forming apparatus such as a copying machine or a printer, the maximum copy density and the gradation deteriorate as the cumulative number of copies increases. This is due to the deterioration of the development contrast due to the deterioration of the latent image carrier, or the deterioration of the developer (toner). On the other hand, in order to increase the developing electric field strength, the gap between the latent image carrier and the developing sleeve is narrowed, the AC component and the DC component of the developing bias are increased, or the exposure light amount is increased to increase the developing contrast. Measures have been taken to increase the size.

[0008]

However, the above-mentioned conventional potential control has the following problems. In the conventional voltage control method, as described above, the control parameters are only the bright portion target potential (VL), the dark portion target potential (VD), and the control coefficient, but it is difficult to correct for obtaining an appropriate image by using only these parameters. . That is, in addition to these parameters,
The change rate of the light part potential of the drum, the change rate of the dark part potential of the drum, the change rate of the control coefficient of the drum, environmental temperature, environmental humidity,
Unless the amount of light of the document illumination lamp and the amount of discharge of the primary charger are taken into consideration, optimum correction cannot be performed.

In particular, the rate of change of the light section potential of the drum, the rate of change of the dark section potential of the drum, and the rate of change of the control coefficient of the drum are important parameters for determining image correction. This is because the light portion target potential, the dark portion target potential, and the control coefficient are different for each drum. Conventionally, these settings are made when the drum is replaced. However, this setting is only the setting of the initial sensitivity of each drum, and the correction with respect to the subsequent change in sensitivity over time is insufficient. In other words, the conventional method has a problem that an optimum correction cannot be performed between a certain correction control time and the next correction control time.

In order to solve the above-mentioned problems, a method has been proposed in which these controls are performed using fuzzy control. That is, as the control parameters, in addition to the light portion target potential (VL), the dark portion target potential (VD), and the control coefficient, the change rate of the light portion potential of the drum, the change rate of the dark portion potential of the drum, and the control coefficient of the drum are controlled. The change rate, the environmental temperature, the environmental humidity, the light amount of the document illumination lamp, the discharge amount of the primary charger, and the like are also set.

By setting these parameters, the drum sensitivity can be optimally corrected, and an appropriate image can be obtained. In particular, by adding the rate of change of the bright part potential of the drum, the rate of change of the dark part potential of the drum, and the rate of change of the control coefficient of the drum to the parameters, the time between a certain correction control time and the next correction control time, Although the optimal correction can be performed, if the number of state quantities is too large, it takes time to calculate the manipulated variable, and there is a problem that it is impossible to keep up with the speed required for the entire potential control system.

Further, in the potential control by the fuzzy control, it takes a long time to calculate an operation amount, and there is a problem that a response speed required for the entire system cannot be obtained. For example, normally, the switching frequency at the switching potential is several hundred KHz, but the calculation speed by fuzzy control cannot follow this frequency. On the other hand, the membership function or the fuzzy rule itself is rewritten according to the control value, the state quantity is divided into several levels, the calculation is performed in advance, and the result is stored in the table memory. However, the response speed is insufficient.

On the other hand, in the above-described conventional image forming apparatus, in controlling the gap between the latent image carrier and the developing sleeve to maintain the maximum copy density, in addition to the change in the state quantity such as the cumulative number of copies, the atmospheric pressure is low. Sometimes, when this gap is narrowed, leakage occurs, or when the gap is narrowed, a developing electric field becomes strong, and there is a problem that fogging occurs in a non-image portion. Further, even if the AC component and the DC component of the developing bias are increased, the developing electric field becomes strong, and fogging occurs in a non-image portion,
There is a problem of causing a leak.

When the gap between the latent image carrier and the developing sleeve is narrowed or the AC component of the developing bias is increased, the developing contrast required for obtaining the maximum copy density may be small. If the amount of exposure for forming is too large, there is a problem that power is wasted and laser deterioration is accelerated. Therefore, it is known that the relationship between the latent image carrier and the developing sleeve, the amount of the developing bias, and the amount of exposure light, which are appropriate for maintaining the maximum copy density and maintaining the gradation, are complicatedly varied. It is difficult to formulate the relationship between the state quantity and the control quantity. Further, if a lookup table or the like is provided for this purpose, the number of tables becomes enormous, and the required memory capacity also increases.

[0015]

An object of the present invention is to provide a fast response speed.
Have to deal with many parameters.
Image processing for which appropriate power control is possible
It is to provide a processing device.

[0017]

In order to achieve the above-mentioned object, an image processing apparatus according to the present invention comprises a detecting means for detecting a state quantity relating to power control, and a qualitative analysis of a state quantity and an operation quantity relating to power control. Storage means for storing the relationship; inference means for inferring the operation amount based on the degree to which the state quantity detected by the detection means belongs to a predetermined set according to the qualitative relationship stored in the storage means; Calculating means for calculating an operation amount without using means, and selecting means for selecting either an inference result of the inference means or a calculation result of the calculation means as a control value relating to power supply control ,
The means is used when the temporal change rate of the state quantity is smaller than a predetermined value.
And selecting an inference result of the inference means.

[0018]

[0019]

[0020]

According to the above configuration, according to the detected state quantity,
Functions to select an appropriate control value.

[0021]

Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. [First Embodiment] Hereinafter, a first embodiment of the present invention will be described in detail. FIG. 1 is a block diagram illustrating a configuration of an image processing apparatus according to a first embodiment of the present invention. In FIG. 1, reference numeral 1 denotes a CPU, which functions as a fitness calculating unit, a calculating unit, and a calculating unit in the apparatus. The fitness calculating means calculates the fitness of the detected state quantity based on the membership function of the state quantity stored in the SRAM 3. The calculating means obtains the inference result of each rule stored in the SRAM 2 by a predetermined calculation based on the calculated conformity. Further, as a calculating means, the operation amount is calculated based on the obtained inference result of each rule.

The counter 1a and the timer 1b are used, for example, when obtaining a detected state quantity, for example, a change rate of the drum light portion potential from the drum light portion potential. Also,
The fuzzy rule change determining unit 1c determines whether the fuzzy rule to be applied has changed, and if it does not change, instructs that the membership function is not called again.

The SRAM 2 stores a fuzzy rule (fuzzy proposition), and the SRAM 3 stores a membership function. The ROM 4 stores a control program of the CPU 1, and the RAM 5 stores the degree of conformity calculation, calculation,
It is used as a calculation work area when performing calculations and the like.
A / D converters 6, 8, 11, 13, 16, 19, 22,
Among the 24, the A / D converters 22, 24, 6, and 11 convert an analog signal from a state quantity detection unit connected thereto, which will be described later, into a digital signal and transmit the digital signal to the CPU 1. On the other hand, the A / D converters 8, 13, 16, and 19, on the contrary,
The digital signal from U1 is converted into an analog signal, and each load is controlled.

The environmental temperature detector 23 and the environmental humidity detector 2
5, the light quantity detection unit 7, and the potential measurement unit 12 function as a state quantity detection unit in the device according to the present embodiment. The document illumination lamp 10, the primary charger 15, the transfer charger 18, and the developing cylinder 21 are to be controlled by this apparatus. Further, the lamp regulator 9, the primary corona current control circuit 14, the transfer corona current control circuit 17, and the developing bias control circuit 20 function as means for driving the above-mentioned controlled object.

The table memory 26 stores in advance the values of the manipulated variables for the combinations of the values of the state variables. Next, a control operation in the image processing apparatus having the above configuration will be described in detail. In the fuzzy control in this embodiment, for example, (a) the light portion potential of the drum (b) the dark portion potential of the drum is used as the state amount, and (c) the primary corona current level control signal is used as the operation amount. .

FIG. 2 shows the membership functions of these sets. Specifically, FIG. 2 (a) shows the membership function of the light potential of the drum, FIG. 2 (b) shows the membership function of the dark potential of the drum, and FIG. 2 (c) shows the primary corona current. 4 shows a membership function of a level control signal. As shown in FIG. 2, each set of the bright portion potential of the drum, the dark portion potential of the drum, and the primary corona current level control signal has three fuzzy sets. For example, for three fuzzy sets of the light portion potential of the drum, the fuzzy labels are labeled “ML”, “MM”, and “MH” (FIG. 2).
(A)), ML (Meibu Deni Low); "Light potential of drum is small"
Fuzzy set MM (Meibu Deni Middle); fuzzy set representing “drum light potential is medium” MH (Meibu Deni High); “drum bright potential is large”
Let be a fuzzy set representing. The degree of belonging to each set is “0”
To an arbitrary value from “1” to “1”.

Therefore, the determination of the primary corona current level control signal in this embodiment using the fuzzy rule will be described. FIG. 5 shows the entire fuzzy rule in the present embodiment. For the determination of the primary corona current level control signal, among them, for example, the following <Rule 5> and <Rule 6>
The fuzzy rule of> is used. That is, <Rule 5> IF (M = MM AND A = AM) T
HEN C = CM <Rule 6> IF (M = MM AND A = AH) T
HEN C = CL where M = bright portion potential of drum A = dark portion potential of drum C = primary corona current level control signal

Now, assuming that the light section potential of the drum, the dark section potential of the drum, and the membership function of the primary corona current level control signal are given as shown in FIGS. 2 (a), 2 (b) and 2 (c), respectively. I do. Then, as shown in FIG. 3, when the light portion potential X0 of the drum and the dark portion potential Y0 of the drum are input,
MM and MM for X0, AM and AH for Y0
Corresponds. Therefore, of the fuzzy rules shown in FIG.
Inference is performed based on Rule 5 and Rule 6.

First, when inferring according to <Rule 6>,
The light portion potential X0 of the drum is included in the set of MMs to the extent of μX0 from the membership function of the light portion potential of the drum. Further, the dark portion potential Y0 of the drum is included in the set of AHs with a degree of μY0 from the membership function of the dark portion potential of the drum. Then, the obtained μX0
And the minimum value of μY0 is determined, and the minimum value is determined as the degree to which the condition part of <Rule 6> is satisfied, and the MIN operation of the value and the membership function of the primary corona current level control signal is performed. The result of this operation is a set S0 (a trapezoid shown by a hatched portion) shown in FIG.

Similarly, when the inference is made in accordance with <Rule 5>, the operation result is a set T0 (a trapezoid shown by oblique lines) shown in FIG. Then, when the inference result of each rule obtained in this way, that is, the set S0 and the set T0 are combined, the combined result becomes a set V0 (shaded portion) shown in FIG. Finally, the center of gravity (point P0) of the set V0 is calculated to obtain a primary corona current level control signal.

Here, these operations are not calculated and obtained each time the operation amount is to be calculated, but are calculated in advance by calculating the operation amount values for the combination of the expected state value values. And store it in the table memory. Then, when it is time to change the operation amount, the operation amount can be determined only by picking up the value in the table memory shown in FIG. 6 from the combination of the detected state amounts. Can be faster.

The table memory is not limited to a two-dimensional memory, but may be three-dimensional depending on the number of state quantities.
Next, an example will be described in which a state quantity that has changed and a state quantity that does not change among some state quantities are distinguished to determine whether a fuzzy rule to be applied changes.

For example, when the value of the light portion potential X of the drum and the value of the dark portion potential Y of the drum change from the value shown in FIG. 3 to the value shown in FIG. 4, that is, the value of X changes from X0 to X1.
Next, it is assumed that the value of Y changes from Y0 to Y1. In this case, the fuzzy rule to be applied changes from <rule 5> and <rule 6> to <rule 3> and <rule 5>, but <rule 5> is used as it is before and after the change. Thereby, it is not necessary to call the membership function (MM, AM, CM used in <Rule 5>) in the SRAM 3 to the CPU 1 again, and this calling procedure can be omitted, so that the response speed is further improved. Can be done.

As described above, according to this embodiment,
Each time it is time to calculate the manipulated variable for performing the potential control, the calculation is not performed, the manipulated variable is calculated in advance for the combination of the values of the expected state variables, and stored in the table memory. At the time when the operation amount should be changed, the operation amount can be determined only by picking up the value in the table memory from the combination of the detected state amounts, so that the response speed can be extremely increased.

In addition, the response speed can be further increased by discriminating the changed state amount from the unchanged state amount among several state amounts and determining whether or not the fuzzy rule to be applied is changed. . The state quantity is not limited to the bright section potential of the drum and the dark section potential of the drum, and any state quantity related to potential control can be used as the state quantity. Also, the operation amount is not limited to the primary corona current level control signal, and the transfer corona current level control signal,
The developing bias level control signal, or the rate of change thereof, may be used.

That is, in order to optimally correct the drum sensitivity and obtain an appropriate image, the control parameters include a light portion target potential (VL), a dark portion target potential (VD), a change rate of the light portion potential of the drum, and a dark portion potential of the drum. , The change rate of the control coefficient of the drum, the light amount of the document illumination lamp, the discharge amount of the temporary charger, and the like. In particular, by adding to the parameters the rate of change of the light part potential of the drum, the rate of change of the dark part potential of the drum, and the rate of change of the control coefficient of the drum, optimal correction is possible even between one correction control time and the next correction control time. Can be performed.

Further, the number of state quantities is not limited to two, and any number can be combined. The above-described fuzzy inference algorithm is merely an example, and the algorithm may be modified. For example, instead of taking the barycenter of the area when combining a plurality of rules, the value on the horizontal axis with respect to the value on the vertical axis may be used as the inference result. Next, a modification of the first embodiment will be described. <Modification 1> FIG. 7 shows the entire fuzzy rule according to Modification 1 of the first embodiment.

Here, as shown in FIG. 7, the temperature O is used instead of the dark portion potential A of the drum. In the same figure, OL, OM, and OH are: OL; a fuzzy set representing “low temperature” OM; a fuzzy set representing “medium temperature” OH; a fuzzy set representing “high temperature” is there.

The method for obtaining the optimum primary corona current level control signal in this modification is the same as the method in the first embodiment, and a description thereof will be omitted. <Modification 2> FIG. 8 is a diagram showing the entire fuzzy rule according to Modification 2, in which S indicates humidity. In the figure, SL, SM, and SH are SL; a fuzzy set representing “low humidity” SM; a fuzzy set representing “medium humidity” SH; a fuzzy set representing “high humidity” .

In this modification, the method of obtaining the optimum primary corona current level control signal is the same as the method in the first embodiment, and the description is omitted. [Second Embodiment] Hereinafter, a second embodiment of the present invention will be described in detail.

FIG. 9 is a block diagram showing a configuration of a power supply device according to a second embodiment of the present invention. In FIG.
Denotes a CPU, which functions as a fitness calculating unit, a calculating unit, a calculating unit, and a driver switching determining unit in the present apparatus. The fitness calculating means calculates the fitness of the detected state quantity based on the membership function of the state quantity stored in the SRAM 33. The calculating means includes a SRAM based on a predetermined calculation based on the calculated fitness.
The inference result of each rule stored in 32 is obtained. Further, as a calculating means, the operation amount is calculated based on the obtained inference result of each rule.

The driver switching determination means includes A / D
From the state quantities taken in via the converters 43 and 46, the driver is set to a control value for normal PWM control, or
A determination is made as to whether or not to use the control value of the fuzzy control. The counter 31a and the timer 31b are used, for example, when determining the rate of change from the detected state quantity, for example, the output voltage of the power supply. The SRAM 32 stores a fuzzy rule (fuzzy proposition), and the SRAM 33 stores a membership function. And the ROM 34 is a CPU
31 for storing the control program.
Is used as a calculation work area when the CPU 31 performs the calculation, calculation, calculation, and the like of the fitness.

Output signal transfer interface (I / O)
36 is a driver switching unit 38
The driver switching unit 38 switches the control value of the PWM control or the control value of the fuzzy control, and outputs it to the driver 39. In addition, the control signal of which switching is performed is as follows.
Driver switching unit 3 from CPU 31 via I / O 37
8 The driver 39 drives the power supply 41 according to the actual operation amount calculated by the PWM control or the fuzzy control. This operation amount is, for example, a duty ratio.

The power supply 41 controls the load 4 based on the above control.
4. For example, output a predetermined voltage to the motor. The output voltage detection unit 42 functions as a state quantity detection unit, and detects an output voltage from the power supply 41. The output voltage detector 42 may be a room temperature sensor or a humidity sensor depending on the case. The load current detection unit 45 also functions as a state quantity detection unit, and detects a value of a current flowing through the load 44 and a state of the load such as a rotation speed of the motor. The A / D converters 43 and 46 convert the analog signals from the output voltage detection unit 42 and the load current detection unit 45 into digital signals and send them to the CPU 31.

Next, the control operation of the power supply device having the above configuration will be described in detail. In the fuzzy control in the present embodiment, for example, (a ′) the output voltage of the power supply, (b) the rate of change of the output voltage of the power supply, and the operation amount, for example, (c) the pulse width of the PWM control Use the duty ratio.

FIG. 10 shows the membership functions of these sets. When the membership function is actually set, the difference between the control target voltage and the output voltage of the power supply (a ') is calculated, and this difference is defined as (a) the voltage deviation. FIG.
(A) is a membership function of the voltage deviation, FIG.
(B) is a membership function of the voltage change rate, and
FIG. 10C shows the voltage control amount, that is, the membership function of the pulse width duty ratio of the PWM control.

As shown in FIG. 10, each set of the voltage deviation, the voltage change rate, and the pulse width duty ratio of the PWM control has three fuzzy sets. For example, voltage deviation 3
For each fuzzy set, the fuzzy label is "V
L "," VM ", and" VH "(FIG. 10)
(A)), respectively, VL (Voltage Low); fuzzy set representing "small voltage deviation" VM (Voltage Middle); fuzzy set representing "medium voltage deviation" VH (Voltage High); It is a fuzzy set representing "large". The degree of belonging to each set is “0”
To an arbitrary value from “1” to “1”. For example, in the case of a fuzzy set with a fuzzy label VM, the voltage deviation 2
The degree of belonging to the set of Vs, that is, the degree of fitness is “1.
0 ", and the degree of conformity with a voltage deviation of 1.5 V or 2.5 V is" 0.5 ".

The determination of the voltage control amount (pulse width duty ratio of PWM control) in this embodiment using the fuzzy rule will be described. FIG. 13 shows the entire fuzzy rule in the present embodiment. In determining the pulse width duty ratio of the PWM control, for example, the following <
The fuzzy rules of Rule 5 and Rule 6 are used.
That is, <Rule 5> IF (V = VM AND R = RM) T
HEND = DM <Rule 6> IF (V = VM AND R = RH) T
HEND = DL where V = voltage deviation R = voltage change rate D = pulse width duty ratio of PWM control.

For example, it is assumed that the membership functions of the voltage deviation, the voltage change rate, and the pulse width duty ratio of the PWM control are given as shown in FIGS. 10 (a), (b) and (c), respectively. Then, as shown in FIG.
0 and the voltage change rate Y0 are input, X0 is V
RM and RH correspond to M and VM, and Y0. Therefore, of the fuzzy rules shown in FIG.
Inference is performed based on Rule 6>.

First, when inferring according to <Rule 6>,
The voltage deviation X0 is included in the set of VMs to the extent of μX0 from the membership function of the voltage deviation. Also,
The voltage change rate Y0 is included in the set of RHs with a degree of μY0 from the membership function of the voltage change rate. Then, the minimum value of the obtained μX0 and μY0 is determined, and the minimum value is defined as the degree of satisfaction of the condition part of <Rule 6>, and the MIN calculation of the value and the membership function of the pulse width duty ratio of the PWM control is performed. Do. The result of this operation is a set S0 (trapezoid shown by hatching) shown in FIG.

Similarly, when inferring according to <Rule 5>, the result of the operation is a set T0 (trapezoidal hatched portion) shown in FIG. Then, when the inference result of each rule obtained as described above, that is, the set S0 and the set T0 are combined, the combined result becomes a set V0 (shaded portion) shown in FIG.
Becomes Finally, the center of gravity (point P0) of the set V0 is calculated, and the pulse width duty ratio of the PWM control is obtained.

Next, an example of switching between normal PWM control and fuzzy control to improve the problem that the calculation speed by fuzzy control cannot keep up with the speed required for the entire control system will be described. Here, when a fast response speed is required and the number of parameters (state quantities) for determining control is small, such as when the voltage rises / falls or when the load current changes drastically, the normal PW
Power control is performed by M control. The response of the load current is not gradual and the response is slow, such as the change over time of the load current. However, since there are many parameters, the normal P
Power control is performed by fuzzy control only when WM control is not sufficient.

The above switching is performed by the CPU 31,
U31 takes in the state quantity of the power supply 41 via the A / D converter 43 and the state quantity of the load 44 via the A / D converter 46, and switches according to the value of these state quantities or a combination thereof. Judge. For example, assuming that the output voltage of the power supply is detected via the A / D converter 43 and the current of the load is detected via the A / D converter 46, the time change rate is calculated from the output voltage value. If it is greater than a certain value, the commercial power supply (AC) is turned ON / OF.
The driver 39 is switched to the normal PWM control on the assumption that the voltage rises / falls by the F control.

However, the rate of change over time is calculated from the current value of the load. If the rate of change over time is smaller than a certain value and the rate of change over time of the output voltage is smaller than a certain value, a fast response speed is not required. And switches the driver to fuzzy control. These determination results are transmitted to the driver switching unit 38 via the I / O 37. After all, normal P
Power supply control is performed by switching between WM control and fuzzy control as occasion demands, and fuzzy control is performed only when there is no sudden change in load and there is an effect due to changes in temperature, humidity, impedance of wiring, and the like.

Next, an example in which a fuzzy rule to be applied is changed when there is a changed state quantity among several state quantities will be described. For example, when the values of the voltage deviation X and the voltage change rate Y change from the values shown in FIG. 11 to the values shown in FIG. 12, that is, the value of X changes from X0 to X1, and Y
Is changed from Y0 to Y1.

In this case, the fuzzy rules to be applied are:
<Rule 5> and <Rule 6> to <Rule 3> and <
It changes to Rule 5; however, <Rule 5> is used as it is both before and after the change. Thereby, the SRAM 3
3 (here, <Rule 5
VM, RM, DM used in>)
It is not necessary to call the caller 1 and this calling procedure can be omitted, so that the response speed can be further improved.

As described above, according to this embodiment,
When a fast response speed is required and the number of parameters (state quantities) that determine the control is small, the power supply is controlled by the ordinary PWM control, and the load current changes slowly and a fast response is not required. Therefore, by performing power control by fuzzy control only when normal PWM control is insufficient, control can be performed with a sufficiently fast response speed in a normal case, and when the number of parameters is large, Since the fuzzy control is performed, fine power control according to the state of the load and the state of the power supply itself can be performed.

The state quantity is not limited to the voltage deviation and the voltage change rate, but may be any state quantity related to power control such as room temperature, humidity, power supply load current, and power supply load current change rate. Can be. Also, the operation amount is PW
The change rate is not limited to the pulse width duty ratio of the M control, and may be the change rate. Furthermore, the number of state quantities is not limited to two,
Any number can be combined.

The above-described fuzzy inference algorithm is an example, and the algorithm may be modified. For example, instead of taking the barycenter of the area when combining a plurality of rules, the value on the horizontal axis with respect to the value on the vertical axis may be used as the inference result. Next, a modified example of the second embodiment will be described. <Modification 1> FIG. 14 shows the entire fuzzy rule according to Modification 1 of the second embodiment.

Here, as shown in FIG. 14, the load current of the power supply is used instead of the voltage change rate R. In the figure, EL, EM, and EH denote EL; a fuzzy set EM representing "the load current of the power supply is small"; a fuzzy set EH representing "the load current of the power supply is medium"; This is a fuzzy set that represents "the current is large."

The method for obtaining the optimum pulse width duty ratio of the PWM control in this modification is the same as the method in the second embodiment, and the description thereof is omitted here. <Modification 2> FIG. 15 is a diagram showing the entire fuzzy rule according to Modification 2, in which F indicates the rate of change of the load current of the power supply. In the figure, FL, FM, and FH are:
FL; fuzzy set representing "the rate of change of the load current of the power supply is small"FM; fuzzy set FH representing "the rate of change of the load current of the power supply is medium"FH;"change rate of the load current of the power supply is large" Is a fuzzy set

In this modification, the method for obtaining the optimum primary corona current level control signal is the same as that in the second embodiment, and a description thereof will be omitted. [Third Embodiment] FIG. 16 is a block diagram showing the configuration of an image forming apparatus according to a third embodiment of the present invention. In the figure, a CPU 101 performs fuzzy control described later,
The RAM 102 is used as a work area when performing fuzzy inference. In addition, the present apparatus has an I / O port 1
04-107, A / D converters 108-110 for converting analog signals into digital signals, motor drive circuits 111,
DC developing bias adjuster 112, AC developing bias adjuster 113, laser driver 114, density sensor for detecting a toner image on a drum, pressure sensor 116, cumulative copy number counter 117, developing unit-latent image carrier unit 200 It is composed of

FIG. 17 is an internal structural view of the developing unit-latent image carrier unit. As shown in FIG.
Latent image carrier 201, developing sleeve 202, motor 20
4. A motor 204 rotates a screw 205 to rotate the developing device mounting table 203.
03 is moved in the direction of the arrow in the figure to control the gap between the latent image carrier and the developing sleeve. The CPU 101 generates a known PWM drive pulse via the I / O port 104, and controls the rotation of the motor 204 in the developing device-latent image carrier unit 200 via the drive circuit 111, so that the above latent image is generated. The gap between the image carrier and the developing sleeve is accurately controlled.

Similarly, the CPU 101 sets the I / O port 1
The DC component of the developing bias is controlled via
The AC component of the developing bias is controlled via the port 106. Further, an exposure amount (full power) of the laser is controlled via the I / O port 107. The development conditions in the apparatus according to the present embodiment include a contrast potential of 400 V, an AC bias V
_PP = 1200 V, frequency 1800 Hz, the reference value of the gap between the latent image carrier and the developing sleeve is 250 μm, and these values are stored in the ROM 102 in advance. The state quantities in this embodiment are (1) the maximum copy density, (2) the atmospheric pressure, (3) the fog amount of the non-image portion, and (4) the cumulative number of copies, and the control amount is the latent image carrier. This is a developing sleeve gap. In this case, the gap between the latent image carrier and the developing sleeve is adjusted so that the maximum copy density becomes the reference value of 1.4 and the "fogging" becomes 2% or less which is the reference value.

The adjustment control of the gap between the latent image carrier and the developing sleeve in this embodiment will be described in detail. FIG. 18 is a diagram illustrating a fuzzy set of the membership functions of the state quantities and the control quantities of (1) to (4) in the present embodiment. As shown in the figure, the maximum copy density, the atmospheric pressure, the fogging amount of the non-image portion, the cumulative number of copies, and the fuzzy set of the latent image carrier and the developing sleeve gap are divided into several parts, and the degree of belonging to each set. Is represented by a value from 0 to 1.

For example, in the case of the gap between the latent image carrier and the developing sleeve, as shown in FIG. 18D, (1) NB (Negative Big): a negative value and a large absolute value (2) NS (Negative Small) ): Negative value and small absolute value (3) Z0 (Zero): around 0 (4) PS (Positive Small): Positive value and small absolute value (5) PB (Positive Big): Positive value Assume that the absolute value is large. Then, the degree of belonging to each set is from 0 to 1.
Expressed by the value up to.

In the present embodiment, the above four state quantities are used, but for simplicity of explanation, three of them, the maximum copy density, the atmospheric pressure, and the non-image fog, are used. For example, in the case of Z0 (Zero) in FIG. 18A, when the maximum copy density is 1.4, the degree of belonging to the set Z0 is 1.0, and the maximum copy density is 1.35, 1.. At the time of 45, the degree of belonging to the set is 0.5.

Next, a method for determining the deviation of the gap between the latent image carrier and the developing sleeve from the maximum copy density, the atmospheric pressure, and the state quantity of fog will be described. The following fuzzy rules are used for the above determination. That is, <Rule 1> IF (maximum copy density = Z0 and
Atmospheric pressure = Z0 and fog = Z0) THEN Latent image carrier-developing sleeve gap deviation = Z0 <Rule 2> IF (maximum copy density = NB and)
Atmospheric pressure = Z0 and fog = Z0) THEN Latent image carrier-developing sleeve gap deviation = Z0 FIG. 19 includes the above <Rule 1> and <Rule 2>.
The figure shows the entire fuzzy rule in the present embodiment, and the symbols in the figure mean A: maximum copy density, B: atmospheric pressure, C: fog, D: deviation between latent image carrier and developing sleeve gap.

FIG. 20 shows a method for inferring the gap deviation between the latent image carrier and the developing sleeve when the maximum copy density is x, the air pressure is y, and the fog is z. As shown in the figure, for <Rule 1>, the membership function of the maximum copy density is included in the set NB to the input x at a degree of μx with respect to the input x, and the membership function of the air pressure is It is included in the set of Z0 with the degree of μy, and is included in the set of Z0 with the degree of μz with respect to the input z according to the fog membership function.

Then, the minimum values of the obtained μx, μy, and μz are obtained, and the MIN calculation of the minimum value and the membership function of the gap deviation between the latent image carrier and the developing sleeve is performed to obtain the set NS. , An operation result indicated by S (hatched portion in the figure) is obtained. By performing the same calculation for <Rule 2>, the calculation result indicated by the hatched portion T in the figure is obtained. Next, the center of gravity of the combined area of S and T is obtained, and the center of gravity is determined by fuzzy logic. Is set as the latent image carrier-developing sleeve gap deviation obtained in. The calculation according to the fuzzy rule is performed once for each copy.

FIG. 21 is a flowchart showing a fuzzy inference processing procedure in this embodiment. In each of steps S1000, S1001, and S1002 in the same figure, the maximum copy density, the atmospheric pressure, and the fog are detected by the density sensor 115 and the atmospheric pressure sensor 116, and step S10 is performed.
03, S1004, and step S1005, FIG.
According to the fuzzy rule shown in FIG. 9, the degree to which the control quantity belongs to the fuzzy set is calculated from the degree to which the state quantity belongs to the fuzzy set by the above-described method.

In step S1006, the center of gravity of the most likely control amount is calculated, and in step S1007,
This center of gravity is set as a latent image carrier-developing sleeve gap deviation. The CPU 101 uses the fuzzy logic P
By moving the motor 204 by the deviation by the WM control so that the gap is set as described above, the latent image is adjusted so that the maximum copy density is 1.4 and the fog is 2% or less with respect to the state amount described above. The gap between the carrier and the developing sleeve is controlled.

As described above, according to the present embodiment,
The fluctuation due to the environment is large, and the state amount and the control amount are governed by an ambiguous relationship.For example, in a developing unit of an image forming apparatus such as a copying machine or a laser beam printer,
In the fuzzy inference, from the state quantities such as the maximum copy density, the atmospheric pressure, the cumulative number of copies, and the fog, which are complicatedly related, the control amount of the latent image carrier-developing sleeve gap, the developing bias amount,
By calculating the appropriate value of the latent image exposure amount, it is possible to control the latent image carrier-developing sleeve gap, the developing bias amount, and the latent image exposure amount according to the state amount, and to increase the maximum copy density without fog. And a stable image with good gradation can be obtained.

In processing, a large-capacity memory such as a look-up table is not required, so that a developing contrast suitable for the latent image carrier and the developing sleeve can be set. Long life and low power consumption can be achieved. [Fourth Embodiment] In the third embodiment, the maximum copy density,
By controlling the gap between the latent image carrier and the developing sleeve with respect to the state quantities such as atmospheric pressure, fog, and the cumulative number of copies, the maximum copy density is maintained by fuzzy control, and an image with little fog is obtained.

However, if the developing conditions are kept constant and the gap between the latent image carrier and the developing sleeve is simply changed (for example, the gap between the latent image carrier and the developing sleeve is reduced), the fog increases sharply and the V-D The slope of the curve increases sharply. As a result, the gradation deteriorates, and the range for leakage becomes very small. Therefore, in this embodiment, the AC bias is changed according to the change in the gap between the latent image carrier and the developing sleeve. For example, the maximum electric field strength is constant (4 v / μm)
The value of the AC developing bias V _PP is changed so as to satisfy the following condition. The latent image carrier-developing sleeve gap (μm ) AC developing bias V _PP (V ) 150 600 180 840 210 1080 250 1400 275 1600 300 1800 When the curve is taken, the characteristic shown in FIG. 22 is obtained. FIG. 23 shows a membership function of the AC developing bias V _PP as a control amount.

As described above, the AC developing bias is controlled in addition to the gap between the latent image carrier and the developing sleeve, and the latent image carrier is controlled.
By changing the AC developing bias in accordance with the value of the developing sleeve gap, a better image can be obtained stably, and the gradation is improved compared to the case where the gap between the latent image carrier and the developing sleeve is simply changed. Is done. In addition, in terms of gradation, it can be changed at the gap between the latent image carrier and the developing sleeve when copying a character or a photograph. <Modification> In the third embodiment, the AC developing bias is also controlled in addition to the gap between the latent image carrier and the developing sleeve. However, as shown in FIG. It can be seen that a small development contrast is required when the development contrast required to reach the copy density changes and the gap between the latent image carrier and the development sleeve is narrow.

Therefore, the exposure amount of the laser or the like can be reduced in accordance with the gap between the latent image carrier and the developing sleeve or the AC developing bias, thereby making it possible to extend the life of the laser and reduce the power consumption. Since the development is not performed with the extra development contrast, the consumption of the extra toner can be prevented. Therefore, in the present modification, in addition to the gap between the latent image carrier and the developing sleeve and the AC developing bias, the exposure amount is also used as the control amount.
Further, in order to control the development contrast, the DC development bias is changed in addition to the exposure amount, and fog control is also performed in addition to the above-described effects. FIG. 24 shows a membership function of the exposure amount and the DC developing bias according to the present modification.

As described above, the range in which the fuzzy control is performed can be expanded by increasing the control amount, and the exposure amount is easily controlled by the laser, and the image scan has better image quality. The method according to this modification is particularly suitable for reversal development. The present invention may be applied to a system including a plurality of devices or to an apparatus including a single device. Also, the present invention
It is needless to say that the present invention can be applied to a case where it is achieved by supplying a program to a system or an apparatus.

[0079]

As described above, according to the present invention, by selecting an appropriate control amount according to the state quantity, it is necessary to cope with a case where a fast response speed is required and a large number of parameters. An image processing apparatus capable of appropriately controlling the power supply in each case can be realized.

[0080]

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of a potential control device according to a first embodiment of the present invention.

FIG. 2 is a diagram illustrating a membership function of a set of state quantities according to the first embodiment.

FIG. 3 is a diagram for explaining a method of determining a primary corona current level control signal in the first embodiment.

FIG. 4 is a diagram for explaining a method of determining a primary corona current level control signal in the first embodiment.

FIG. 5 is a diagram showing the entire fuzzy rule in the first embodiment.

FIG. 6 is a diagram showing a table memory for storing a value of a state quantity and a value of an operation amount in the first embodiment.

FIG. 7 is a diagram illustrating an entire fuzzy rule according to a first modification of the first embodiment;

FIG. 8 is a diagram illustrating an entire fuzzy rule according to a second modification of the first embodiment;

FIG. 9 is a block diagram illustrating a configuration of a power supply device according to a second embodiment of the present invention.

FIG. 10 is a diagram showing a membership function of a set in the second embodiment.

FIG. 11 is a diagram for explaining a method of determining a pulse width duty ratio of PWM control in the second embodiment.

FIG. 12 is a diagram for explaining a method of determining a pulse width duty ratio of PWM control in the second embodiment.

FIG. 13 is a diagram showing the entire fuzzy rule in the second embodiment.

FIG. 14 is a diagram illustrating an entire fuzzy rule according to a first modification of the second embodiment;

FIG. 15 is a diagram illustrating an entire fuzzy rule according to a second modification of the second embodiment;

FIG. 16 is a block diagram illustrating a configuration of an image forming apparatus according to a third embodiment of the present invention.

FIG. 17 is an internal structural diagram of a developing device-latent image carrier unit according to a third embodiment.

FIG. 18 is a diagram showing a fuzzy set of membership functions of state quantities and control quantities in the third embodiment.

FIG. 19 is a diagram showing the entire fuzzy rule in the third embodiment.

FIG. 20 is a diagram illustrating a method of inferring a latent image carrier-developing sleeve gap deviation in the third embodiment.

FIG. 21 is a flowchart illustrating a fuzzy inference processing procedure in the third embodiment.

FIG. 22 is a diagram illustrating a VD curve according to a fourth example.

FIG. 23 is a diagram illustrating a membership function of an AC developing bias V _PP as a control amount according to the fourth embodiment.

FIG. 24 is a membership function of an exposure amount and a DC developing bias according to a modification of the fourth embodiment.

[Explanation of symbols]

1 CPU 1a Counter 1b Timer 1c Fuzzy Rule Change Judgment Unit 2, 3 SRAM 4 ROM 4 5 RAM 7 Light Amount Detection Unit 6, 8, 11, 13, 16, 19, 22, 24 A / D
Converter 9 Lamp regulator 10 Original illumination lamp 12 Potential measurement unit 15 Primary charger 18 Transfer charger 17 Transfer corona current control circuit 20 Developing bias control circuit 21 Developing cylinder 23 Environmental temperature detector 25 Environmental humidity detector 26 Table memory

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-4-291274 (JP, A) JP-A-2-8903 (JP, A) JP-A-4-268601 (JP, A) JP-A-3- 87764 (JP, A) JP-A-1-142902 (JP, A) JP-A-4-39703 (JP, A) JP-A-4-107604 (JP, A) JP-A-1-293402 (JP, A) JP-A-5-303405 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB name) G03G 15/00 G03G 21/00 G03G 21/14 G06K 15/14 G05B 13/02 G06F 9 / 44

Claims (3)

(57) [Claims] A detection unit configured to detect a state quantity related to power control; a storage unit configured to store a qualitative relationship between the state quantity and an operation amount related to power control; and the qualitative information stored in the storage unit. According to the relationship, inference means for inferring the operation amount based on the degree to which the state quantity detected by the detection means belongs to a predetermined set, and calculation means for calculating the operation amount without using the inference means, And selecting means for selecting any of the inference result of the inference means or the calculation result of the calculation means as a control value relating to the power supply control , wherein the selection means has a temporal change rate of the state quantity that is smaller than a predetermined value.
Select the inference result of the inference means when it is smaller
The image processing apparatus according to claim. 2. The image processing apparatus according to claim 1, wherein the operation amount includes a duty ratio. 3. The image processing apparatus according to claim 1, wherein the state quantity includes an output voltage from a power supply.