JP3178865B2 - Active noise control 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 active noise control apparatus for actively reducing noise in a passenger compartment of an automobile, a passenger compartment of an aircraft, and the like.

[0002]

2. Description of the Related Art Conventionally, as an active noise control device of this type, there is, for example, one shown in FIG. 14 of British Patent Publication No. 2149614.

This conventional apparatus is applied to a cabin of an aircraft or a closed space similar to the cabin. The closed apparatus 101 includes loudspeakers 103a, 103b, 103c and microphones 105a, 105b, 105c, 105d. Control sounds that cause noise to interfere are generated by the speakers 103a, 103b, and 103c, and residual signals (residual noise) are measured by the microphones 105a, 105b, 105c, and 105d. These loudspeakers 103a, 103b, 103c and microphones 105a, 105b, 105c, 105d are connected to a signal processor 107. The signal processor 107 is connected to the microphone 105a, 105b and the fundamental frequency of the noise source measured by the fundamental frequency measuring means. , 105c, 105
d and receives the input signal from the loudspeakers 103a, 1 so that the sound pressure level in the closed space 101 is minimized.
A drive signal is output to the terminals 03b and 103c.

Here, three loudspeakers 103a, 103b, and 103c and four microphones 105a, 105b, 105c, and 105d are provided in the closed space 101, respectively. 10
3a and 105a are provided one by one.
Assume that the transfer function from the noise source to the microphone 105a is H, and the loudspeaker 103a is connected to the microphone 10a.
The transfer function to 5a is C, the sound source information signal noise source produces a X _p, the noise signal E as a residual noise which is observed by the microphone 105a is a _{E = X p · H + X} p · G · C Become. Here, G is a transfer function required for silencing. When the noise is completely canceled at the point to be silenced (the position of the microphone 105a), E = 0.
At this time, G becomes: G = −H / C. As the filter coefficient, G at which the microphone detection signal E is minimized is obtained, and based on this G, the filter coefficient in the signal processor 107 is adaptively updated. As a method of obtaining a filter coefficient so as to minimize the microphone detection signal E, there is an LMS algorithm (Least Mean Square) which is a kind of the steepest descent method.

[0005] When a plurality of microphones are installed as shown in FIG.
Control is performed so that the sum of the signals detected at a, 105b, 105c, and 105d is minimized.

Here, the LMS algorithm will be described more specifically. l-th microphone 105a
The noise signal detected by (105b,...) Is represented by e _l (n),
When there is no control sound from the loudspeakers 103a, 103b, 103c, the l-th microphone 105a (10
5b,...), The noise signal detected by e _pl (n), the transfer function (FIR) between the m-th loudspeaker 103a (103b,.
(Finite impulse response) function j-th (j = 0, 1,
2,..., I _c -1) are represented by a digital filter with a filter coefficient of C _lmj , a reference signal, ie, a sound source information signal X _p (n), and a reference signal X _p (n). The ith (i = 0, 1, 2, 1,..., I _k ) of the adaptive filter that drives the loudspeakers 103a (103b,.
If the coefficient of -1) is W _mi ,

[0007]

(Equation 1)

The following holds.

Next, the evaluation function (variable to be minimized) Je
To

[0010]

(Equation 2)

[0011]

[0012] Then, for determining the filter coefficients W _m of the evaluation function Je minimizing adopting LMS algorithm. In other words, the evaluation function Je a value obtained by partially differentiating each filter coefficient W _mi updates the filter coefficient W _mi.

Therefore, from equation (2),

[0014]

(Equation 3)

From the equation (1),

[0016]

(Equation 4)

Thus, the right side of the equation (4) is

[0018]

(Equation 5)

If so, the rewriting equation of the filter coefficient can be obtained by the LMS algorithm of the following equation (6).

[0020]

(Equation 6)

As is evident from this form, the stability and convergence of this algorithm are:

[0022]

(Equation 7)

And the convergence coefficient α.

[0024]

By the way, in the above control, the above equation (6) depends on the characteristics of the system to be controlled and the setting of the microphone in the system, etc. The transfer function C _im from the microphone in the space to the loudspeaker is treated as being constant.

However, the microphones 103a and 103b and the loudspeaker 1
When the phase characteristics of 01a and 101b change, the transfer function C _im changes, and the convergence characteristic of equation (5) becomes extremely acute. When the condition worsens, the sound pressure rises at the evaluation point. In addition, not only an ideal silencing effect cannot be obtained due to a so-called divergent state, but also noise may be increased and deteriorated.

[0026] In order to prevent such divergence, as an index representing the level of divergence, stop control when the sum of absolute values or square values of the adaptive filter coefficients W _mi exceeds a predetermined threshold I do. Or the adaptive filter coefficient W
Reset _mi . Alternatively, it is conceivable to provide a divergence prevention logic that changes the control convergence coefficient and the like.

However, according to the experimental results of the inventors,
Since the sound pressure level of vehicle interior noise varies depending on the engine speed and the transfer characteristics between the loudspeaker and the microphone vary depending on the frequency, optimal adaptation when the sum of the squares of the sound pressure input to the microphone is minimized. The values of the filter coefficients do not always have a constant distribution at all engine speeds, but show different distributions at each engine speed, as shown in FIG.

The sum of the squares of the sound pressure input to the microphone is minimized not only by the engine speed but also by various conditions such as the load of the engine, the driving pattern, the running speed of the vehicle, and the temperature in the passenger compartment. The value of the optimal adaptive filter coefficient varies significantly.

Therefore, if the threshold value is set to a constant value with respect to various conditions such as the engine speed, the sum of the absolute value or the square value of the optimum value of the adaptive filter coefficient is originally calculated. Under various conditions such as the engine speed that is distributed at a value close to the threshold value or a value larger than the threshold value, the divergence state cannot be achieved due to the variation in the probability density distribution of the optimal value of the adaptive filter coefficient. It is conceivable that the divergence prevention logic operates with a high probability.

Also, under various conditions such as the number of revolutions of the engine in which the sum of the absolute value or the square of the optimum value of the adaptive filter coefficient is distributed at a value sufficiently small with respect to the threshold value, the divergence state In this case, the adaptive filter coefficient does not exceed the threshold, and the occupant hears the divergent secondary sound, which may cause considerable discomfort.

Therefore, the present invention suppresses the divergence of the device,
An object of the present invention is to provide an active noise control device capable of more appropriate noise control.

[0032]

In order to solve the above-mentioned object, a first aspect of the present invention is a control sound source which is provided in a closed space and generates a control sound which interferes with noise to reduce noise at an evaluation point. Means for detecting a residual noise at a predetermined position after the interference, means for detecting a signal relating to the noise generation state of the noise source, and outputting a signal for driving the noise source based on the signal with a predetermined filter coefficient An adaptive filter, and control means for changing a filter coefficient of the adaptive filter using a steepest descent algorithm having a predetermined convergence coefficient based on an output signal of the residual noise detection means and an output signal of the noise generation state detection means. An active noise control device, comprising: means for detecting a control environment in which the noise control is performed;
Means for detecting a divergence state level of the device, and divergence state stopping means for stopping the divergence state when the divergence state level detected by the divergence state detection means exceeds a predetermined threshold value; The value is set so as to change according to the control environment of the control environment detecting means.

According to a second aspect of the present invention, there is provided a control sound source which is provided in a closed space and generates a control sound which interferes with noise to reduce noise at an evaluation point, and means for detecting residual noise at a predetermined position after the interference. Means for detecting a signal relating to the noise generation state of the noise source, an adaptive filter for outputting a signal for driving the control sound source based on the signal with a predetermined filter coefficient, and an output signal and noise of the residual noise detection means Control means for changing the filter coefficient of the adaptive filter using a steepest descent algorithm having a predetermined convergence coefficient based on the output signal of the occurrence state detection means, and Means for detecting a control environment to be performed, means for detecting a divergence state level of the device, and a divergence state level detected by the divergence state detection means is a predetermined threshold value. And means for reducing the interruption or the convergence coefficient control when was example, the threshold is characterized in that it is set to change in response to changes in the controlled environment of the control environment detection means.

According to a third aspect of the present invention, the divergence state level is a sum of absolute values of filter coefficients of the adaptive filter.

According to a fourth aspect of the present invention, the divergence state level is a sum of squares of filter coefficients of the adaptive filter. The drive signal is characterized by:

According to a sixth aspect of the present invention, the divergence state level is an output signal of the residual noise detecting means.

According to a seventh aspect of the present invention, the control environment detecting means is the noise generation state detecting means.

The invention of claim 8 is characterized in that the control environment detecting means is means for detecting the state of the closed space.

According to a ninth aspect of the present invention, the means for detecting the state of the closed space is a means for detecting the state of a vehicle.

[0040]

According to the first aspect of the present invention, the control means uses a steepest descent algorithm having a predetermined convergence coefficient on the basis of the output signal of the residual noise detection means and the output signal of the noise generation state detection means. Change the coefficient. The adaptive digital filter outputs a signal for driving the control sound source with a predetermined filter coefficient based on a signal relating to a noise generation state. As a result, the control sound source can generate a control sound that interferes with the noise, thereby reducing the noise at the evaluation point.

At this time, the divergence state detecting means detects the divergence state level, and when the detected divergence state level exceeds a predetermined threshold value which is set so as to change according to the change of the control environment, the divergence state is detected. The divergence is stopped by the state stopping means. As a result, appropriate noise control can be performed.

According to the second aspect of the present invention, the divergence state detecting means detects a divergence state level, and sets a predetermined threshold value set such that the detected divergence state level changes in accordance with a change in the control environment. If so, the changing means interrupts control or reduces the convergence coefficient. As a result, appropriate noise control can be performed.

According to the third aspect of the present invention, the sum of the absolute values of the filter coefficients of the adaptive filter is defined as a divergence state level, and when the divergence state level exceeds a predetermined threshold, the changing means interrupts the control or sets the convergence coefficient. Decrease.

According to a fourth aspect of the present invention, the sum of the squares of the filter coefficients of the adaptive filter is defined as a divergence state level, and when the divergence state level exceeds a predetermined threshold, the changing means interrupts the control or sets the convergence coefficient. Decrease.

According to the fifth aspect of the present invention, the drive signal of the control sound source is set to a divergence state level, and when the divergence state level exceeds a predetermined threshold value, the changing means interrupts the control or reduces the convergence coefficient.

According to the sixth aspect of the present invention, the detection signal of the residual noise detecting means is a divergence state level, and when the divergence state level exceeds a predetermined threshold value, the changing means interrupts the control or reduces the convergence coefficient.

In the invention according to claim 7, the noise generation state detection means is a control environment detection means, and the threshold value is changed according to a detection result of the noise generation state detection means, that is, a change in the control environment.

In the present invention, the means for detecting the state of the closed space is the control environment detecting means, and the threshold value is changed according to the detection result of the means for detecting the state of the closed space.

In the ninth aspect of the present invention, the means for detecting the state of the closed space is a means for detecting the state of the vehicle, and the threshold value is changed according to the state.

[0050]

Embodiments of the present invention will be described below. In addition,
The description will be made using the interior of the vehicle as an example.

FIG. 1 is a block diagram of an active noise control device according to a first embodiment of the present invention. A loudspeaker 3 as a control sound source and a residual noise detecting means are provided in a vehicle interior 1 which is a closed space. Microphones 5 are connected to a microprocessor 7 as control means. The microprocessor 7 has an LMS algorithm 9 and an adaptive filter 11, and the microphone 5 is an LMS
In the algorithm 9, the loudspeakers 3 are connected to adaptive filters 11, respectively.

The microphones 5 are installed at, for example, front and rear positions of the ceiling of the passenger compartment 1 so as to output analog voltage noise signals corresponding to residual noise (sound pressure) at the respective installation positions. Has become.

The loudspeaker 3 is installed below the instrument panel of the passenger compartment 1 and behind the rear seat, and receives a driving signal output from the microprocessor 7 to control sound in the passenger compartment 1. (Acoustic signal).

The noise in the passenger compartment 1 is, for example, the engine 1
Reference numeral 3 denotes a noise source. As the noise generation state detecting means, for example, a rotation speed sensor 15 for detecting a rotation speed of a crankshaft is used, and a detected rotation speed signal is input to the adaptive filter 11 as a reference signal Xp. It has become so. The noise generation state detection means only needs to detect a signal relating to the noise generation state of the noise source.
For example, an output signal of a vibration sensor provided on the outer surface of the engine, an ignition pulse signal of the engine, a crank angle signal detected by a crank angle signal sensor, a signal detecting vibration of a suspension, a signal detecting wind noise, etc. Can also be used.

In the LMS algorithm 9, the reference signal Xp detected by the rotation speed sensor 15 and the microphone 5
Using the output e and the predetermined convergence coefficient α

[0056]

(Equation 8)

Is performed, and the filter coefficient _Wmi of the adaptive filter 11 is sequentially changed so as to minimize the sum of squares of the noise signal e (n) detected by the microphone 5 as the residual noise.

The adaptive filter 11 receives the reference signal Xp, filters the signal, and outputs a drive signal to the loudspeaker 3. A control sound having a phase opposite to that of the noise in the passenger compartment 1 is output from the loudspeaker 3, and residual noise is detected by the microphone 5 by causing interference with the noise. Thus, the adaptive filter 11 has a structure which outputs a signal y that drives the loudspeaker 3 as a control sound based on the signal related to noise generation state by predetermined filter coefficient W _mi.

The microprocessor 7 as a control means determines a predetermined convergence coefficient α based on the output signal of the microphone 5 as the residual noise detecting means and the output signal of the crank angle signal sensor 15 as the noise generation state detecting means. Adaptive filter 1 using steepest descent algorithm 9
The configuration is such that the filter coefficient W _{mi of} 1 is changed.

On the other hand, in this embodiment, the microprocessor 7 constitutes a divergence state detecting means for detecting a divergence state level of control by a predetermined threshold value, and the detection level of the divergence state detection means is a predetermined value. A change means for interrupting the control when the threshold value is exceeded or reducing the convergence coefficient is provided. In this embodiment, for example, the sum of the absolute values of the filter coefficients of the adaptive filter 11 or the sum of the square values is used as the divergence state level. The divergence state level is a detection signal of the noise generation state detection means, for example, a rotation speed signal detected by a rotation speed sensor, an output signal of a vibration sensor provided on an outer surface of the engine, an ignition pulse signal of the engine, a crank angle. It is also possible to use a crank angle signal detected by a signal sensor, a signal detecting suspension vibration, a signal detecting wind noise, and the like.

The microprocessor 7 has a table for changing the threshold value of the sum of the absolute values of the filter coefficients as the divergence state level or the sum of the square values, for example, using the engine speed as a parameter. The table is, for example, as shown in FIG. 2, and the threshold value is obtained by using a probability density distribution of an adaptive filter coefficient when optimal control is performed for each engine rotation speed.
Set to a desired value that does not malfunction during the operation of the divergence prevention logic, for example, the sum of the absolute values or the sum of the squares of the adaptive filter coefficients with a probability of not exceeding a predetermined number of times N during the operation of the divergence prevention logic. Have been.

The parameter for changing the threshold value is as follows:
Any environment in which noise control is performed may be used.For example, the load of the engine, the running speed of the vehicle, the driving pattern, the input level from the noise source, the frequency of the noise source, the temperature in the passenger compartment, the occupant state, and the open / close state of windows. And the like of the vehicle.

Further, the parameter for changing the threshold value is not limited to one item of the control environment. For example, as shown in FIGS. 3 and 4, a combination of two items of the engine speed and the engine load, Alternatively, a combination of two items of the engine rotation speed and the temperature in the vehicle interior can be used as a parameter. Further, as shown in FIG. 5, multiple items such as the engine rotation speed, the engine load, and the temperature in the vehicle interior are combined. The threshold value can be changed as a parameter.

In this embodiment, as a control environment detecting means for detecting an environment in which noise control is performed, a rotation speed sensor 15 of the engine 13 which is the noise generation state detecting means is used in combination.

Next, the operation of the above embodiment will be described with reference to the flowcharts shown in FIGS.

FIG. 6 shows the sum of the absolute values of the adaptive filter coefficients as the divergence state level.

That is, in FIG.
_{In 61} , the rotation speed of the engine 13 is detected by the rotation speed sensor 15, and a threshold value of the divergence state detection level set for each engine rotation speed is selected from the rotation speed based on, for example, a table shown in FIG. Step _S62 ).

In step S ₆₃ , the sum of the absolute values of the adaptive filter coefficients of the adaptive filter 11 updated by the LMS algorithm 9 is calculated.

Next, in step _S64 , the sum of the absolute values of the adaptive filter coefficients is compared with the threshold value of the divergence state detection level, and it is determined whether the sum of the absolute values of the adaptive filter coefficients exceeds the threshold value. Is done. If exceed the absolute value of the sum threshold of the adaptive filter coefficients, returns because those eligible to noise control is being carried out without incurring any divergence to step S ₆₁ and step S _63.

[0070] the sum of the absolute value of the adaptive filter coefficients by counting the number of times n is exceeded in step S ₆₅ if exceeds the threshold in step S _64, a predetermined number of times n is set in advance is exceeded in step S ₆₆ N Is determined. If the number of times n does not exceed the predetermined number of times N, it is determined that the diverging state has not been reached, and step _{S61 is performed.}
And Back to S _63.

[0071] In step S _66, the number surpassed n disrupts the control determines that falls into a divergent state if exceeds a predetermined number N (step S _67). By doing so, it is possible to suppress the divergence phenomenon without misidentifying or not detecting the divergence state over the entire rotation speed of the engine 13. Therefore, it becomes possible to reduce the vehicle interior noise more reliably.

FIG. 7 shows the sum of the square values of the adaptive filter coefficients as the divergence state level.

[0073] Since the basic flow of control other differ only step S ₇₄ is the same as that shown in FIG. 6, and will not be repetitively described are denoted by the same step numbers S1 to S7. In this embodiment, since the sum of the squares of the adaptive filter coefficients is used as it is as the detection of the divergence state level, the calculation is simplified, and the rapid rise of the divergence phenomenon can be responded more quickly. It is.

FIGS. 8 to 13 show a second embodiment.

In this embodiment, the applied voltage Ve of the loudspeaker 3 is used as the divergence state level, and the temperature in the passenger compartment, the running speed of the vehicle, and the occupant riding state are used as parameters for changing the threshold value.

That is, as shown in FIG. 8, the noise in the passenger compartment 1 is, for example, road noise as a noise source. For example, a suspension vibration sensor 17 is used as a noise generation state detecting means. Are input to the adaptive filter 11 via the A / D converter 19.

As control environment detecting means, a vehicle speed sensor 21 for detecting the running speed of the vehicle and an occupant riding state sensor 23 for detecting the occupant riding state are provided. / D converter 2
The data is input to the microprocessor 7 via the input terminals 5 and 27. The vehicle speed sensor 21 detects a vehicle speed by, for example, receiving a signal from a speedometer. The occupant riding state sensor 23 also serves as a means for detecting a state in the passenger compartment 1, which is a closed space. For example, a seat switch provided for each seat or a buckle switch provided for each seat belt is provided. By taking in the signal, the occupant riding state of each seat is detected.

In this embodiment, the loudspeaker 3
Is applied to the microprocessor 7 via the D / A converter 29. The microprocessor 7 sets, for example, the applied voltage Ve of the loudspeaker 3 to a diverging state level, and changes the threshold value of the applied voltage to the loudspeaker 3, which is the diverging state level, using, for example, the vehicle speed, the vehicle interior temperature, and the occupant riding state as parameters. Has a table. The table is, for example, as shown in FIGS. 9 to 12, when there is one occupant, when there are two occupants, when there are three occupants, when there are four occupants, and the like. The loudspeaker is set to a desired value that does not cause malfunction, for example, a voltage applied to the loudspeaker with a probability of not exceeding a predetermined number of N times or more during the operation of the divergence prevention logic.

FIG. 13 is a flowchart showing the operation of the above embodiment.

First, in step _S131 , the vehicle speed is detected by the vehicle speed sensor 21, and in step _S132 , the occupant riding state sensor 23 detects the occupant riding state such as whether there is one or two occupants. Then, in step _S133 , the detected vehicle speed and the occupant riding state are, for example, shown in FIGS.
Based on the table indicated by 2, the divergence state detection threshold value set for each number of occupants and each vehicle speed is reversed.

On the other hand, in step _S134 , the applied voltage Ve of the loudspeaker 3 is detected.

Next, in step _S135 , the voltage applied to the speaker is compared with the threshold value, and it is determined whether the voltage applied to the speaker exceeds the threshold value. If the speaker application voltage does not exceed the threshold value, the noise control is properly performed without any divergence state, and the process returns to step _S131 and step _S134 .

[0083] counts the number of times n of loudspeakers applied voltage in step ₁₃₅ exceeded in step S ₁₃₆ if exceeds the threshold, whether exceeding a predetermined number of times N the number of times n is exceeded in step S ₁₃₇ is determined in advance is determined . If the number of times n does not exceed the predetermined number N, it is determined that the diverging state has not occurred, and the process returns to steps _S131 and _S134 .

[0084] In step S _137, the number of times higher than the n
If the number exceeds a predetermined number N, it is determined that a divergence state has occurred, and the flow shifts to step _S138 to decrease the convergence coefficient.

Therefore, in this embodiment, any vehicle speed,
In the occupant riding state, the divergence phenomenon can be suppressed without misidentifying or not detecting the divergence state.
Therefore, the vehicle interior noise can be more reliably reduced as in FIGS.

[0086]

As is clear from the above, according to the configuration of the present invention, the threshold value of the divergence state level for detecting the divergence state of the apparatus is set so as to change in accordance with the change in the environment in which the noise control is performed. With this configuration, it is possible to suppress the divergence of the device and perform more appropriate noise control without erroneously recognizing or not detecting the divergence state in all environments where noise control is performed.

[Brief description of the drawings]

FIG. 1 is a block diagram according to a first embodiment of the present invention.

FIG. 2 is a table showing an example of a change in threshold value for divergence state detection used in the first embodiment.

FIG. 3 is a table showing an example of a change in threshold value for divergence state detection.

FIG. 4 is a table showing an example of a change in a threshold value for divergence state detection.

FIG. 5 is a table showing an example of a change in a threshold value for divergence state detection.

FIG. 6 is a flowchart according to the first embodiment of the present invention.

FIG. 7 is a flowchart according to another embodiment.

FIG. 8 is a block diagram according to a second embodiment of the present invention.

FIG. 9 is a table showing an example of a change in threshold value for divergence state detection used in the second embodiment.

FIG. 10 is a table showing an example of a threshold value change of divergence state detection used in the second embodiment.

FIG. 11 is a table showing an example of a threshold value change of divergence state detection used in the second embodiment.

FIG. 12 is a table showing an example of a threshold value change in divergence state detection used in the second embodiment.

FIG. 13 is a flowchart according to a second embodiment of the present invention.

FIG. 14 is a block diagram according to a conventional example.

[Explanation of symbols]

Reference Signs List 1 vehicle compartment (closed space) 3 loudspeaker (control sound source) 5 microphone (residual noise detection means) 7 microprocessor (control means, divergence state detection means, change means) 15 rotation speed sensor (noise generation state detection means, control environment) Detection means) 17 Suspension vibration sensor (Noise generation state detection means) 21 Vehicle speed sensor (Control environment detection means) 23 Passenger boarding state sensor (Control environment detection means)

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-3-263573 (JP, A) JP-A-2-225969 (JP, A) JP-A-4-11291 (JP, A) (58) Field (Int.Cl. ⁷ , DB name) G10K 11/178 B60R 11/02 B64C 1/40

Claims (9)

(57) [Claims] 1. A control sound source provided in a closed space for generating a control sound that interferes with noise to reduce noise at an evaluation point, means for detecting residual noise at a predetermined position after the interference, and a noise source Means for detecting a signal relating to a noise generation state, an adaptive filter for outputting a signal for driving the noise source based on the signal by a predetermined filter coefficient, and an output signal of the residual noise detection means and a noise generation state detection means. A control means for changing a filter coefficient of the adaptive filter using a steepest descent algorithm having a predetermined convergence coefficient based on an output signal, and detecting a control environment in which the noise control is performed. Means, a means for detecting a divergence state level of the device, and a divergence state when the divergence state level detected by the divergence state detection means exceeds a predetermined threshold value. An active noise control device, comprising: a divergence state stopping means for stopping the noise, wherein the threshold value is set so as to change in accordance with the control environment of the control environment detecting means. 2. A control sound source provided in a closed space for generating a control sound that interferes with noise to reduce noise at an evaluation point, means for detecting residual noise at a predetermined position after the interference, and a noise source Means for detecting a signal relating to a noise generation state, an adaptive filter for outputting a signal for driving the control sound source based on the signal by a predetermined filter coefficient, and an output signal of the residual noise detection means and a noise generation state detection means. Control means for changing the filter coefficient of the adaptive filter using an algorithm of the steepest descent having a predetermined convergence coefficient based on the output signal,
Means for detecting a control environment for performing the noise control, means for detecting a divergence state level of the device, and interruption of control when the divergence state level detected by the divergence state detection means exceeds a predetermined threshold value Alternatively, there is provided a means for reducing the convergence coefficient, and the threshold value is set so as to change in accordance with a change in the control environment of the control environment detecting means. 3. The active noise control device according to claim 1, wherein the divergence state level is a sum of absolute values of filter coefficients of the adaptive filter. 4. The active noise control device according to claim 1, wherein the divergence state level is a sum of squares of filter coefficients of the adaptive filter. 5. The active noise control device according to claim 1, wherein the divergence state level is a drive signal of the control sound source. 6. The active noise control device according to claim 1, wherein said divergence state level is a detection signal of said residual noise detection means. 7. The active noise control device according to claim 1, wherein said control environment detection means is said noise generation state detection means. 8. The active noise control device according to claim 1, wherein said control environment detecting means is means for detecting a state of said closed space. 9. The vehicle according to claim 7, wherein the means for detecting the state of the closed space is a means for detecting a state of a vehicle.
The active noise control device as described in the above.