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Claims  |
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I claim:
1. An adaptive controller comprising:
an IIR adaptive filter model with an error input that depends on a model
error signal which is a combination of an error signal from an error
sensor, a filtered correction signal which is generated by filtering a
correction signal used to create a secondary input that combines with a
system input to yield a system output, and a model output signal from the
adaptive IIR filter model.
2. In an adaptive control system having an output transducer that receives
a correction signal from an adaptive controller and outputs a control
signal that combines with a system input to yield a system output, and an
error sensor that senses the system output and outputs an error signal to
the adaptive controller, an improvement in the adaptive controller
comprising:
a correction signal filter that receives the correction signal and outputs
a filtered correction signal;
an uncancelled equation error summer that receives the error signal and the
filtered correction signal and outputs an uncancelled equation error
signal;
a reference signal filter that receives a reference signal and outputs a
filtered reference signal;
an adaptive filter model that receives the filtered reference signal and
outputs a model output signal;
a model error summer that receives the uncancelled equation error signal
and the model output signal, and outputs a model error signal that is used
to adapt the adaptive filter model;
a copy of the adaptive filter model that receives the reference signal and
outputs the correction signal;
an input sensor that senses the system input and outputs an input signal to
the adaptive controller;
an adaptive D filter model that receives the correction signal and outputs
a D model output signal; and
a reference signal summer that receives the input signal from the input
sensor and the D model output signal and outputs the reference signal.
3. In an adaptive control system having an output transducer that receives
a correction signal from an adaptive controller and outputs a control
signal that combines with a system input to yield a system output, and an
error sensor that senses the system output and outputs an error signal to
the adaptive controller, an improvement in the adaptive controller
comprising:
a correction signal filter that receives the correction signal and outputs
a filtered correction signal;
an uncancelled equation error summer that receives the error signal and the
filtered correction signal and outputs an uncancelled equation error
signal;
a reference signal filter that receives a reference signal and outputs a
filtered reference signal;
an adaptive filter model that receives the filtered reference signal and
outputs a model output signal;
a model error summer that receives the uncancelled equation error signal
and the model output signal, and outputs a model error signal that is used
to adapt the adaptive filter model; and
a copy of the adaptive filter model that receives the reference signal and
outputs the correction signal;
wherein the uncancelled equation error signal is also used as the reference
signal.
4. In an adaptive control system having an output transducer that receives
a correction signal from an adaptive controller and outputs a control
signal that combines with a system input to yield a system output, and an
error sensor that senses the system output and outputs an error signal to
the adaptive controller, an improvement in the adaptive controller
comprising:
a correction signal filter that receives the correction signal and outputs
a filtered correction signal;
an uncancelled equation error summer that receives the error signal and the
filtered correction signal and outputs an uncancelled equation error
signal;
a reference signal filter that receives a reference signal and outputs a
filtered reference signal;
an adaptive filter model that receives the filtered reference signal and
outputs a model output signal;
a model error summer that receives the uncancelled equation error signal
and the model output signal, and outputs a model error signal that is used
to adapt the adaptive filter model; and
a copy of the adaptive filter model that receives the reference signal and
outputs the correction signal;
wherein the adaptive filter model is an IIR filter.
5. An adaptive control system having a system input and a system output,
the system comprising:
a plurality of n output transducers each receiving one of n correction
signals and outputting a secondary input that combines with the system
input to yield the system output;
a correction signal filter having p.times.n channels, the correction signal
filter receiving n correction signals and outputting p filtered correction
signals;
a plurality of p error sensors, each error sensor sensing the system output
and outputting an error signal;
a plurality of p uncancelled equation error summers, each uncancelled
equation error summer receiving one of the p error signals and one of the
p filter correction signals and outputting an uncancelled equation error
signal;
an adaptive filter model having p adaptive elements corresponding to each
of n.times.m filter model channels, each of the p.times.n.times.m adaptive
elements outputting an element output signal;
a reference signal filter corresponding to each adaptive filter model
element, each reference signal filter receiving one of m reference signals
and outputting a filtered reference signal to the corresponding adaptive
filter model element;
a plurality of p model output summers, each summing n.times.m element
output signals to yield p model output signals for each model output
summer;
a plurality of p model error summers, each receiving an uncancelled
equation error signal from one of the uncancelled equation error summers
and a model output signal from one of the model output summers, and
outputting one of p model error signals wherein each model error signal is
used to update each of the n.times.m channels in the adaptive filter
model; and
a copy of the adaptive filter model that receives the m reference signals
and outputs the n correction signals.
6. The system as recited in claim 5 further comprising a plurality of m
input sensors, each sensing the system input and outputting an input
signal that is used as one of the m reference signals.
7. The system as recited in claim 5 further comprising:
a plurality of m input sensors each sensing the system input and outputting
an input signal;
an adaptive D filter model that receives the n correction signals and
outputs a plurality of m D Model output signals; and
a plurality of m reference signal summers each receiving an input signal
and a D model output signal and outputting one of the m reference signals.
8. A system as recited in claim 5 wherein the p uncancelled equation error
signals are also used as the m reference signals.
9. A system as recited in claim 5 wherein the adaptive control system is an
active acoustic attenuation system, the system input is an input acoustic
wave, and the system output is an output acoustic wave.
10. A system as recited in claim 9 wherein the active acoustic attenuation
system is a sound attenuation system, the output transducers are
loudspeakers, and the error sensors are microphones.
11. A system as recited in claim 9 wherein the active acoustic attenuation
system is a vibration control system, the output transducers are shakers,
and the error sensors are accelerometers.
12. An adaptive control method in an active control system having a system
input and a system output comprising the steps of:
generating a control signal from a correction signal;
combining the control signal with the system input to yield the system
output;
sensing the system output and generating an error signal in response
thereto;
filtering the correction signal to yield a filtered correction signal;
combining the filtered correction signal and the error signal to yield an
uncancelled equation error signal;
filtering a reference signal to yield a filtered reference signal;
processing the filtered reference signal through an adaptive filter model
to generate a model output signal;
combining the uncancelled equation error signal and the model output signal
to yield a model error signal;
adapting the adaptive filter model at least in part in response to the
model error signal;
processing the reference signal through a copy of the adaptive filter model
to generate the correction signal;
sensing the system input and generating an input signal in response
thereto;
processing the correction signal through a D model to generate a D model
output signal; and
combining the D model output signal and the input signal to generate the
reference signal.
13. An adaptive control method in an active control system having a system
input and a system output comprising the steps of:
generating a plurality of n control signals, each from one of n correction
signals; signal;
combining the control signals with the system input to yield the system
output;
sensing the system output and generating a plurality of p error signals in
response thereto;
processing the n correction signals through a copy of a p.times.n C model
to generate p filtered correction signals;
combining the p error signals and the p correction signals to yield p
uncancelled equation error signals;
separately processing each of a plurality of m reference signals through
each of p.times.n channels of a copy of the C model to generate
m.times.p.times.n filtered reference signals;
processing the filtered reference signals through an adaptive filter model
to generate a plurality of p model output signals;
combining the p uncancelled equation error signals and the p model output
signals to generate p model error signals;
using the p model error signals to adapt the adaptive filter model; and
processing the m reference signals through a copy of the adaptive filter
model to generate the n correction signals. |
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Claims |
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Description |
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BACKGROUND
The invention is a fast adapting control system and method that is
particularly useful for tracking in an active acoustic attenuation system.
Active acoustic attenuation involves injecting a canceling acoustic wave to
destructively interfere with and cancel a system input acoustic wave to
yield a system output acoustic wave. In an active acoustic attenuation
system, an adaptive control filter receives a reference signal and in turn
supplies a correction signal to an output transducer such as a loudspeaker
in a sound application or a shaker in a vibration application. The output
transducer injects the canceling acoustic wave or secondary input to
destructively interfere with the system input so that the system output is
zero or some other desired value.
The system output acoustic wave is sensed with an error sensor such as a
microphone in a sound system, or an accelerometer in a vibration system.
The error sensor generates an error signal in response to the system
output. An error input signal, which depends at least in part on the error
signal, is supplied to the adaptive control filter, and adaptive
parameters in the control filter are updated in relation to the error
input signal to adapt the filter. A convergence factor or step size
parameter .mu. is normally selected to ensure convergence of the adaptive
control filter.
It is important that the adaptive control filter in an active acoustic
attenuation system be stable (i.e. converge), and also that the adaptive
filter be robust. One consideration in this respect, is that the adaptive
control filter account for propagation delay and phase shifts in an
auxiliary path between the output of the adaptive control filter and the
output of the error sensor. The filtered-X least-means-square (LMS) and
the filtered-U recursive-least-means-square (RLMS) update methods as
described in U.S. Pat. No. 4,677,676 which is incorporated herein by
reference, account for the delay and phase shifts in the auxiliary path
when updating the adaptive control filter model, and are effective means
of providing adaptive control in many active acoustic attenuation systems.
In the filtered-X and filtered-U methods, it is normally preferred that C
modeling of the auxiliary path be accomplished adaptively on-line such as
described in above incorporated U.S. Pat. No. 4,677,676. Other methods
such as delayed inverse C modeling, or delayed Hermetian transpose C
modeling can also be used to account for delay and phase shift in the
auxiliary path.
Even if these methods are used, propagation delay in the auxiliary path can
cause some instability in the adaptive control filter model if the
convergence factor or step size .mu. is too large.
SUMMARY OF THE INVENTION
The invention provides a method of adapting an adaptive control system in
which the effect of propagation delay through the auxiliary path is
eliminated from the adaptation process. The maximum stable step size .mu.
can therefore be increased, and the adaptive filter control model can thus
be more robust.
The invention can be embodied in an adaptive controller having an adaptive
filter model with an error input, and no transfer functions experiencing
propagation delay or phase shifts between the output of the adaptive
filter model and the error input to the adaptive filter model. This
adaptive control scheme is implemented by using a copy of the adaptive
filter model that inputs a reference signal, and outputs a correction
signal that drives the output transducer. The correction signal also
inputs a correction signal filter which is preferably a copy of a C model
to generate a filtered correction signal. The filtered correction signal
is combined with an error signal from an error sensor to generate an
uncanceled equation error signal which is an estimate of what the system
output would be in the absence of a secondary input into the system from
the output transducer. This uncanceled equation error signal can be
combined with a model output signal from the adaptive filter model to
generate a model error signal that is used to adapt the adaptive filter
model.
A copy of the C model is preferably provided before the adaptive filter
model, rather than after the adaptive filter model. This is possible
because both the C model and the adaptive filter model are slowly
adapting. The adaptive filter model can therefore adapt without
consideration of propagation delay or phase shifts due to transfer
functions in the auxiliary path between the output of the adaptive filter
model and the error input to the adaptive filter model.
The invention can be implemented in a feedforward system, or a feedback
system. The invention can also be implemented in a multiple input,
multiple output, and multiple error (MIMO) system.
While the invention is useful for active acoustic attenuation such as sound
or vibration attenuation, the invention is also useful for other adaptive
control applications in which there are transfer functions in the
auxiliary path.
BRIEF DESCRIPTION OF THE DRAWINGS
Prior Art
FIG. 1 is a schematic illustration of an adaptive control system
implementing a filtered-X LMS update as is known in the art.
FIG. 2 is a schematic illustration of an adaptive control system
implementing an LMS update with delayed inverse C modeling as is known in
the art.
Present Invention
FIG. 3 is a schematic illustration of a feedforward adaptive control system
in accordance with the invention.
FIG. 4 is a schematic illustration showing a preferred embodiment of the
system shown in FIG. 3.
FIG. 5 is a schematic illustration of a feedback adaptive control system in
accordance with the invention.
FIG. 6 is a schematic illustration showing a feed forward multiple input,
multiple output, multiple error system in accordance with the invention.
FIG. 7 is a schematic illustration showing a feedback multiple input,
multiple output, multiple error system in accordance with the invention.
DETAILED DESCRIPTION
Prior Art
FIG. 1 shows an active acoustic attenuation system 10 with a feedforward
adaptive control system implementing a filtered-X LMS update in the time
domain. In the system 10 shown in FIG. 1, an input sensor 22 generates a
reference signal x(k) that is processed in an adaptive M filter 12 to
generate a correction signal y(k). The correction signal y(k) is
transmitted to a summing junction 13 where it is summed with low level
random noise from a random noise source 15. The correction signal y(k)
from the summing junction 13 is then transmitted to an output transducer
18. The output transducer 18 outputs a secondary input (i.e., a canceling
acoustic wave) that combines with the system input (i.e., an input
acoustic wave) to yield the system output (i.e., an output acoustic wave).
An error sensor 34 senses the system output and generates an error signal
e(k) in response thereto.
An auxiliary path between the output of the adaptive M filter 12 and the
output of the error sensor 34 is modeled on line by C model 11. Low level
random noise from random noise source 15 is transmitted in line 17 to C
model 11, which outputs a signal in line 19. Summer 21 subtracts the
signal in line 19 from the error signal in line 23, and outputs a signal
in line 25. The signal in line 25 is transmitted to multiplier 29 where it
is multiplied with low level random noise in line 27. The multiplier 29
outputs an error input signal 31 which is transmitted to C model 11 to
update the adaptive parameters in the C model 11.
The reference signal x(k) is filtered through a copy 42 of the C model 11,
and the resultant filtered-X reference signal is transmitted through line
43 to multiplier 36. The error signal e(k) is also transmitted to
multiplier 36 through line 33. The multiplier outputs an error input
signal in line 45 to the adaptive M filter 12.
In the above acoustic attenuation system 10 shown in FIG. 1, the adaptive M
filter 12 is typically a transversal finite impulse response (FIR) filter.
However, as described in incorporated U.S. Pat. Nos. 4,677,676, and
4,677,677 which is also incorporated by reference, the adaptive M filter
12 can be an infinite impulse response (IIR) filter. If the adaptive M
filter 12 is an IIR filter, the filtered-U recursive-least-means-square
(RLMS) update method should be used as disclosed in U.S. Pat. No.
4,677,676. The filtered-X or filtered-U update methods can be implemented
in a feedforward system as shown in FIG. 1, or in a feedback system. In a
feedback system, the error signal e(k) or a derivation thereof, can be
used as the reference signal x(k).
FIG. 2 shows another feedforward system 110 implementing the LMS or RLMS
update method for active acoustic attenuation. The system 110 in FIG. 2 is
an inverse C model system 110 as is also described in U.S. Pat. No.
4,677,676. The system 110 in FIG. 2 is similar in many respects to the
filtered-X system shown in FIG. 1, and like reference numbers are used
where appropriate to facilitate understanding.
In FIG. 2, a delay element 46 replaces the copy 42 of the C model 11 shown
in FIG. 1. Also, a delayed inverse C model filter 48 is added in FIG. 2 to
filter the error signal e(k). Depending on the application, it may be
quite burdensome or even impossible to process a C model inverse on-line.
Under many circumstances it may be preferred to implement a delayed
Hermetian transpose C model in place of a delayed inverse C model 48, as
disclosed in copending patent application entitled "Adaptive Control
System with a Corrected Phase Filter Error Update", U.S. Ser. No.
08/297,241 by Steven R. Popovich.
The systems 10 and 110 shown in FIGS. 1 and 2 correlate a delayed or
filtered reference signal x(k), normally called a regressor, with the
error signal e(k) or a filtered version thereof, to account for delay and
phase changes in the auxiliary path so that the adaptive M filter 12
converges. A convergence factor or step size .mu. is multiplied times the
error input signal in line 45 before adapting the adaptive weights in the
M filter 12 to ensure convergence.
Present Invention
FIGS. 3-7 show the invention which is a fast adapting control system. The
invention is particularly useful for tracking in an active acoustic
attenuation system, however the invention may be used in other control
system applications.
Referring to FIG. 3, the invention is shown in conjunction with a
feedforward active sound attenuation system 1. An input microphone 22
senses a system input such as an input acoustic wave, and generates a
reference signal x(k) in line 50. The reference signal x(k) in line 50 is
transmitted to a copy 52 of an adaptive M filter model 54. The reference
signal x(k) is processed by the copy 52 of the M filter model 54 to
generate a correction signal y(k) in line 56. The correction signal y(k)
is transmitted through line 58 to drive an output transducer 18.
The output transducer 18 outputs a secondary input that combines with the
system input to yield the system output. The secondary input in this
active sound attenuation system can be called a canceling acoustic wave.
In non-acoustic control applications, the secondary input is analogous to
a control signal.
The system output is sensed by an error microphone 34 which generates an
error signal e(k). The error signal e(k) is transmitted in line 60 to an
uncanceled equation error summer 62. The correction signal y(k) is not
only transmitted to the output transducer 18, but is also transmitted
through line 64 to input a C model copy 66. The correction signal y(k) in
line 64 is filtered through the C model copy 66, and C model copy 66
outputs a filtered correction signal in line 68. The filtered correction
signal in line 68 is summed in summing junction 62 with the error signal
e(k) in line 60 to yield an uncanceled equation error signal in line 70.
It is preferred that the C model copy 66 be a copy of an adaptive on-line
C model as described in above incorporated U.S. Pat. No. 4,677,676. The C
model should model the transfer function between the output of the copy 52
of the adaptive M filter model 54 and the error sensor 34, which is
referred to herein as the auxiliary path. The uncanceled error equation
signal in line 70 is thus an estimate of what the system output would be
if no secondary input from the output transducer 18 were injected into the
system 1.
The reference signal x(k) is not only transmitted to the copy 52 of the
adaptive M filter model 54, but is also transmitted in line 72 to a
reference signal filter 74 which is also preferably C model copy. The C
model copy reference signal filter 74 is preferably a copy of the same C
model or the C model copy correction signal filter 66. The C model copy 74
outputs a filtered reference signal in line 76. The adaptive M filter
model 54 inputs the filtered reference signal and outputs a model output
signal in line 78. The model output signal in line 78 is subtracted from
the uncanceled equation error signal in line 70 in summer 80 to yield a
model error signal in line 82. The filtered reference signal in line 76 is
also transmitted to a multiplier 84. The model error signal in line 82 is
input to the multiplier 84 where it is multiplied by the filtered
reference signal to yield an error input signal in line 86. The error
input signal in line 86 is input to the adaptive M filter model 54 to
adapt the model 54. It can be appreciated that the model error signal in
line 82 is an estimate of the error signal e(k) in line 60. This is
because both are adaptive M filter model 54 and the C model copy reference
signal filter 74 are in general slowly adapting. Since there are no
transfer functions in the path from the output of the adaptive M filter
model 54 until the generation of the model error signal in line 82, there
is no need to account for propagation delay or phase shifts in auxiliary
path during adaptation of M filter model 54. In some systems, this may
allow the use of a larger step size .mu. without risking instability.
The adaptive M filter model 54 in system 1 of FIG. 3 can have various
forms. For instance, the M filter 54 can be a direct FIR filter. Another
embodiment of the invention with an IIR filter is shown in FIG. 4. The
system 1 in FIG. 4 has three adaptive filters: a direct FIR A filter model
88, a recursive FIR B filter model 90, and a recursive D filter model 92.
The adaptive D model 92 inputs the correction signal y(k) and outputs a D
model output signal that is subtracted from an input signal from the input
microphone 22 in summer 94 to yield reference signal x(k). The adaptive D
model can be adapted on-line using a random noise technique similar to
that for adaptive on-line C modeling as described in U.S. Pat. No.
4,677,676.
Still referring to FIG. 4, the reference signal x(k) inputs a copy 96 of
the A filter 88. The copy 96 of the A filter 88 outputs a signal in line
98 to summer 100. A copy 102 of the recursive B filter 90 receives the
correction signal y(k) as model input, and outputs a signal in line 104
that is summed with the signal in line 98 in summer 100 to yield the
correction signal y(k).
The A filter model 88 inputs the filtered reference signal from line 76 and
outputs a signal in line 106 to summer 108. The summer 108 sums the signal
in 106 and a signal from the B filter model 90 in line 110 to yield the
model output signal in line 112. The recursive B filter model 90 inputs
the model output in line 112. The model error signal in line 82 is
multiplied by the model output signal in line 112 by multiplier 114 which
provides an error input signal in 116 to adapt B filter model 90. The
error signal in line 82 is also provided to multiplier 118 where it is
multiplied by the filtered reference signal in line 76 to provide an error
input signal in line 120 to adapt the A filter model 88. In other
respects, the system in FIG. 4 is similar to the system in FIG. 3, and
like reference numerals have been used where appropriate.
FIG. 5 shows an equation error feedback active acoustic attenuation system
2 implementing the invention. The system 2 in FIG. 5 is similar in many
respects to the system 1 in FIG. 3 and like reference numerals were used
where appropriate to facilitate understanding. The system 2 in FIG. 5 does
not have an input sensor 22 like the system in FIG. 3, but rather uses the
uncanceled equation error signal in line 70 as transmitted in lines 122
and 124 as the reference signal x(k). The signal in line 70, which is used
as a reference signal in the system, is transmitted in line 72 to the
reference signal filter 74 as in the system 1 in FIG. 3. The uncanceled
equation error signal that is transmitted from summer 62 through line 70
and 122 is also transmitted through line 126 to the model error summer 80.
In other respects, the system 2 in FIG. 5 is similar to the system 1 shown
in FIG. 3.
FIG. 6 shows a feedforward, multiple input, multiple output (MIMO) system 3
implementing the invention. In general, a feedforward MIMO system 3 has a
plurality of m input sensors represented by 22a and 22b, a plurality of n
output transducers represented by 18a and 18b, and a plurality of p error
sensors represented by 34a and 34b. The MIMO system 3 in FIG. 6 can be an
m.times.n.times.p system but is shown as a 2.times.2.times.2 system for
the sake of example. The MIMO system 3 in FIG. 6 is analogous to the
single input single output (SISO) system in FIG. 3, and like reference
numbers with corresponding a and b designations are used where appropriate
to facilitate understanding.
Input sensor 22a senses the system input to generate a reference signal
x.sub.1 (k) in line 50a, and input sensor 22b senses the system input to
generate a reference signal x.sub.2 (k) in line 50b. The reference signals
are input to model copy 52 which has a plurality of n.times.m channels.
The model copy 52 is shown in FIG. 6 to be a direct FIR filter, however
other filters such as an IIR filter can be used if desired. In FIG. 6, the
model copy 52 has four channels: A.sub.11, A.sub.12, A.sub.21, and
A.sub.22 ; and two summers: 123a and 123b (i.e. n=2). A correction signal
y.sub.1 (k) is output from summer 123a of the model copy 52 through line
56a. Likewise, a correction signal y.sub.2 (k) is output from summer 123b
of model copy 52 in line 56b. The correction signal y.sub.1 (k) is
transmitted in line 58a to drive output transducer 18a, and is also
transmitted through line 64a to C model copy 66. Correction signal y.sub.2
(k) is transmitted in line 58b to drive output transducer 18b, and also
through line 64b to C model copy 66. C model 66 has four channels (i.e.
p.times.n), and two summers 124a and 124b (i.e. p=2). An error sensor 34a
senses the system output and generates an error signal e.sub.1 (k) in line
60a. An error sensor 34b senses the system output and generates an error
signal e.sub.2 (k) in line 60b. Uncanceled equation error summer 62a sums
the error signal. e.sub.1 (k) in line 60a with the output from the C model
copy 66 in line 68a to yield an uncanceled equation error signal in line
70a. Uncanceled equation error summer 62b sums the error signal e.sub.2
(k) in line 60b with the filtered correction signal in line 68b to yield
an uncanceled equation error signal in line 70b. FIG. 6 shows two (2)
uncanceled equation error signals, but in general the number of equation
error signals should equal the number of error sensors generating error
signals.
A model output signal my.sub.1 in line 78a is subtracted from the
uncanceled equation error signal in line 70a in summer 80a to yield a
model error signal me.sub.1 in line 82a. A model output signal my.sub.2 in
line 78b is subtracted from the uncanceled equation error signal in line
70b in summer 80b to yield model error signal me.sub.2 in line 82b. The
model error signals me.sub.1 and me.sub.2 are used to adapt the adaptive
channels in the model 54.
Reference signal x.sub.1 (k) is also transmitted to a reference signal
filter 74a through line 72a where it is processed through four (i.e.
p.times.n) channels of a C model copy. The reference signal x.sub.1 (k) in
line 72a is processed through each channel of the C model copy 74a
separately to generate four (i.e. p.times.n) filtered reference signals,
r.sub.111, r.sub.121, r.sub.211, and r.sub.221. The filtered reference
signal r.sub.111 is input to the adaptive filter model channel A.sub.11 to
generate an element output signal that is transmitted to summer 130a.
Filtered reference signal r.sub.121 is processed through adaptive filter
model channel A.sub.21 to generate an element output signal that is
transmitted to summer 130a. Filtered reference signal r.sub.211 is
processed through adaptive filter model channel A.sub.11 to generate an
element output signal that is transmitted to summer 130b. Filtered
reference signal r.sub.221 is processed through adaptive filter channel
A.sub.21 to generate an element output signal that is transmitted to 130b.
In a similar fashion, reference signal x.sub.2 (k) is transmitted through
line 72b to a reference signal filter 74b, and is processed through each
separate channel of C model copy to generate filtered reference signals
r.sub.112, r.sub.122, r.sub.212, and r.sub.222. The filtered reference
signal r.sub.112 is processed through adaptive filter model channel
A.sub.12 to generate an element output signal that is transmitted to
summer 130a. A filtered reference signal r.sub.122 is processed by
adaptive filter model channel A.sub.22 to generate an element output
signal that is transmitted to summer 130a. The filtered reference signal
r.sub.212 is processed through adaptive filter model channel A.sub.12 to
generate an element output signal that is transmitted to summer 130b. The
filtered reference signal r.sub.222 is processed through adaptive filter
model channel A.sub.22 to generate an element output signal that is
transmitted to summer 130b. The summer 130a outputs model output signal
my.sub.1 in line 78a. The summer 130b outputs model output signal my.sub.2
in line 78b. FIG. 6 shows two model output summers, 130a and 130b, but in
general there are a plurality of p model output summers.
Each adaptive filter model channel A.sub.ij is adapted using each of the p
model error signals me.sub.1 and me.sub.2 (i.e. p=2 in FIG. 6). For
instance, the preferred method of adapting for the adaptive filter model
channels A.sub.11, A.sub.21, A.sub.12, and A.sub.22 can be represented by
the following equations:
A.sub.11 : (r.sub.111 me.sub.1)+(r.sub.211 me.sub.2) (1)
A.sub.12 : (r.sub.112 me.sub.1)+(r.sub.212 me.sub.2) (2)
A.sub.21 : (r.sub.121 me.sub.1)+(r.sub.221 me.sub.2) (3)
A.sub.22 : (r.sub.122 me.sub.1)+(r.sub.222 me.sub.2) (4)
Where the symbol represents a multiplier for correlating a regressor (i.e.
r.sub.ijk) and a model error signal (i.e. me.sub.i) in an LMS update. In
general, there are n.times.m adaptive filter model channels A.sub.ij, and
each is updated using each of the p model error signals.
FIG. 7 shows a feedback MIMO system 4. The system 4 in FIG. 7 is similar in
many respects to the system 3 in FIG. 6, and like reference numbers are
used where appropriate. Like the SISO feedback system 2 shown in FIG. 5,
the MIMO system 4 in FIG. 7 uses the uncanceled equation error signals in
lines 70a and 70b as model input signals in lines 72a and 72b. In
addition, uncanceled equation error signal in line 70a is transmitted
through lines 122a and 124a to be used as a reference signal to the model
copy 52. Likewise, the uncanceled equation error signal in line 70b is
transmitted through lines 122b and 124b to be used as a reference signal
to the model copy 52. The uncanceled equation error signals in lines 70a
and 70b are also transmitted through lines 122a and 122b and through lines
126a and 126b, to the model error summers 80a and 80b. In this system, the
number of reference signals equals the number of error sensors. In other
respects, the system 4 in FIG. 7 can be implemented similar to the system
3 in FIG. 6.
It is recognized that various equivalents, alternatives and modifications
are possible within the scope of the appended claims. For instance, while
this preferred embodiment shows the invention implemented in an active
sound attenuation system, the invention as disclosed, can be used in other
active control applications.
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