U.S. patent application number 11/037794 was filed with the patent office on 2008-06-12 for systems and methods for shock compensation utilizing an adaptive control technique algorithm.
Invention is credited to Simeon Masson.
Application Number | 20080140316 11/037794 |
Document ID | / |
Family ID | 38157815 |
Filed Date | 2008-06-12 |
United States Patent
Application |
20080140316 |
Kind Code |
A1 |
Masson; Simeon |
June 12, 2008 |
SYSTEMS AND METHODS FOR SHOCK COMPENSATION UTILIZING AN ADAPTIVE
CONTROL TECHNIQUE ALGORITHM
Abstract
A method for providing dynamic disturbance compensation to an
inertial system is described. The method includes determining
estimated correction factors based on received acceleration
components, and dynamically determining filter coefficients for a
filter configured to receive velocity and position signals and
output a prediction error. The method further includes combining
the estimated correction factors and the prediction error into
adjustment factors, where the prediction error is configured to be
a feedback control signal, and applying the adjustment factors to
compensate the inertial system such that effects of the dynamic
disturbance are removed.
Inventors: |
Masson; Simeon; (Tampa,
FL) |
Correspondence
Address: |
HONEYWELL INTERNATIONAL INC.
101 COLUMBIA ROAD, P O BOX 2245
MORRISTOWN
NJ
07962-2245
US
|
Family ID: |
38157815 |
Appl. No.: |
11/037794 |
Filed: |
January 18, 2005 |
Current U.S.
Class: |
701/510 |
Current CPC
Class: |
G01C 21/16 20130101;
G01C 25/005 20130101 |
Class at
Publication: |
701/220 |
International
Class: |
G01C 21/00 20060101
G01C021/00 |
Claims
1.-14. (canceled)
15. A control system configured to provide dynamic disturbance
compensation to an inertial system, said system comprising: an
estimator configured with calibrated navigational estimates and
further configured to receive acceleration data from the inertial
system and estimate correction factors based on received
acceleration data; a filter configured to receive velocity and
position signals from the inertial system, said filter further
configured with a linear predictive coding algorithm which
determines coefficients for said filter, said filter providing
filter compensated velocity and position signals; and a corrector
configured to receive the estimated correction factors and the
filter compensated velocity and position signals, said corrector
further configured to detect errors related to acceleration
variations and compute adjustments to compensate for the
acceleration variations, said adjustments provided as a feedback
control system to the inertial system, thereby providing dynamic
disturbance compensation.
16. A control system according to claim 15 wherein said estimator
is configured to validate attitude, velocity, and position
estimates against calibration and navigational data updates.
17. A control system according to claim 15 wherein said filter is
configured to validate attitude, velocity, and position predictions
against calibration and navigational data updates.
18. A control system according to claim 15 further comprising a
shock attenuator drive providing drive signals to the inertial
system, wherein said corrector is configured to apply the computed
adjustments to said shock attenuator drive.
19. A control system according to claim 15 wherein said estimator
comprises a Kalman filter.
20. A control system according to claim 15 wherein said estimator
is configured to: predict changes to the correction factors since
the previous estimation of correction factors; and correct the
predicted changes utilizing a state-space model.
21. A control system according to claim 15 wherein said estimator
is configured to: integrate acceleration data once to determine a
velocity; and integrate acceleration data twice to determine a
position.
22. A control system according to claim 15 wherein the acceleration
data received by said estimator is representative of six
dimensional state variables with respect to a space fixed reference
frame used in conjunction with a direction cosine matrix.
23. A control system according to claim 15 wherein to implement the
linear predictive coding functions algorithm said filter comprises
a re-configurable field programmable gate array technique.
24. A control system according to claim 23 wherein said filter
implements predictive coding functions based on orthogonality
linear predictions.
25. A control system according to claim 23 wherein said filter is
configured to determine a prediction error based on a difference
between an estimate from the linear predictive coding functions
algorithm and a sample value.
26. A control system according to claim 15 wherein said filter
comprises a finite impulse response (FIR) filter, said filter
configured to utilize the linear predictive coding algorithm
configured to determine coefficients which minimize a prediction
error.
27.-40. (canceled)
Description
BACKGROUND OF THE INVENTION
[0001] This invention relates generally to flight control systems,
and more specifically, to methods and systems for providing dynamic
disturbance compensation for a flight platform, for example, shock
compensation during a flight utilizing adaptive control
techniques.
[0002] An inertial sensor assembly (ISA), typically includes an
inertial measurement unit (IMU) that detects acceleration and
rotation in three planes. A typical IMU includes three
accelerometers and three rotational rate sensors arranged with
their input axes in a perpendicular relationship. The
accelerometers and sensors are generally rigidly and precisely
mounted within a housing along with other related electronics and
hardware. Commonly, the housing is mounted to a support or chassis
through suspension mounts or vibration isolators. The chassis is
rigidly and precisely mounted to a frame of a vehicle, such as an
aircraft or missile. An ISA typically forms a portion of a flight
control system.
[0003] Certain components of flight control systems, for example,
the above described inertial measurement units (IMUs), are likely
to experience performance degradation when exposed to motion as a
result of body bending and induced vibration. Such motions are
typically high shock transients at low frequencies. Example
applications where such shock transient conditions are encountered
include missile and other interceptor applications. In missile and
interceptor flight control systems, the IMU is likely to sustain
shock wave transients at accelerations up to multiple G levels over
a period of time. These shock wave transients, when above
predefined and specified thresholds, may be destructive to the IMU.
However, the IMU is required to provide accurate and reliable
navigation in order to achieve mission success. Consequently, an
IMU is called upon to operate reliably in a highly vibratory
environment accommodating low frequency/high amplitudes and high
frequency/low amplitudes conditions. Therefore, accelerations
sensed by the IMU due to missile vibration are to be resolved into
the IMU chosen navigation reference frame.
BRIEF SUMMARY OF THE INVENTION
[0004] In one aspect, a method for providing dynamic disturbance
compensation to an inertial system is provided. The method
comprises determining estimated correction factors based on
received acceleration components, and dynamically computing filter
coefficients for a filter configured to receive velocity and
position signals and output a prediction error. The method further
comprises synthesizing estimated correction factors and the
prediction error into adjustment factors, where the prediction
error is configured to be a feedback control signal to compensate
the inertial system such that effects of the dynamic disturbance
are attenuated.
[0005] In another aspect, a control system configured to provide
dynamic disturbance compensation to an inertial system is provided.
The control system comprises an estimator configured with
navigational estimates and a filter configured to receive velocity
and position signals from the inertial system. The estimator is
further configured to receive acceleration data from the inertial
system and estimate correction factors based on received
acceleration data. The filter is further configured with a linear
predictive coding algorithm configured to determine coefficients
for the filter that provides compensated velocity and position
signals. The control system further comprises a corrector
configured to receive the estimated correction factors and the
filter compensated velocity and position signals. The corrector is
further configured to detect errors related to acceleration
variations and compute adjustments to compensate for the
acceleration variations.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] FIG. 1 is a block diagram of an inertial measurement
unit.
[0007] FIG. 2 is a block diagram of a dual mode shock compensator
control system for inertial measurement units.
[0008] FIG. 3 is a flow chart illustrating operation of the dual
mode shock compensator control system of FIG. 2.
DETAILED DESCRIPTION OF THE INVENTION
[0009] At least some known inertial measurement units, sometimes
referred to as IMU packages, are not currently capable of surviving
shocks and vibrations that result from accelerations exceeding
certain acceleration (G) levels. The systems and methods described
herein provide in-system dynamic compensation to known IMU packages
and reduce the sensitivity of such IMU packages to high shock and
vibration levels. The systems and methods are also applicable to
other systems that require control and attenuation of high shock
and vibration levels.
[0010] FIG. 1 is a block diagram of an inertial measurement unit
(IMU) 10. IMU 10 includes accelerometers 12 and gyroscopes 14 in a
sensor block 15 providing inertial data to a processing block 16
which includes at least one analog to digital converter (not
shown). In a typical embodiment, accelerometers 12 includes three
orthogonal accelerometers and gyroscopes 14 includes three
orthogonal gyroscopes.
[0011] Various types of accelerometers and gyroscopes are known. In
the embodiment illustrated, data from accelerometers 12 and
gyroscopes 14 is processed by processing 16. IMU 10 further
includes digital outputs 18 providing at least one acceleration
output (digitized delta theta 20) for utilization by systems
external to IMU 10. Processing block 16 further provides digitized
velocity outputs 22 and digitized position outputs 24 for
utilization by external systems. Processing block 16 may also
provide additional data relating to gyroscope 14 operation to one
or more analog outputs (not shown.
[0012] FIG. 2 is a block diagram of a dual mode shock compensator
control system 50 which is incorporated in an inertial measurement
unit, for example IMU 10 (also shown in FIG. 1). As illustrated, an
IMU shock level compensator 51 provides IMU data, specifically,
digitized, sensed data including acceleration, velocity, and
displacement, as determined by IMU 10 to an attitude, velocity,
position sensor processing block 52 which in turn provides the
acceleration, velocity and position data to an adaptive control
technique algorithm (ACTA) 54. Sensor processing block 52 also
receives navigation calibration data 55.
[0013] In one embodiment, ACTA 54 incorporates a re-configurable
field programmable gate array (FPGA) technique implementing a
linear predictive coding functions algorithm. The linear predictive
coding functions algorithm dynamically determines coefficients for
a finite impulse response (FIR) filter within ACTA 54. In one
embodiment, the linear predictive coding functions algorithm is an
estimation algorithm, which implements prediction functions based
on orthogonality linear prediction. Such an implementation involves
determining a prediction error by determining a difference between
the estimate and the sample value. The error is then directly
correlated to the summation of a set of linear product terms
consisting of predictor coefficients and the sample value.
Predictor coefficients are then determined using a least squares
approach.
[0014] The FIR filter then compensates, or weighs, the velocity and
position signals originating from the sensors within the IMU. The
compensation of the velocity and position signals, based on the
linear predictive coding functions algorithm, results in FIR filter
coefficients that are dynamically computed and synthesized. The
dynamic computation of the FIR filter coefficients ensures that an
output of the FIR filter is a minimal prediction error. As such,
output characteristics of the filter result in estimates of optimal
coefficients at specific times based on the best prediction and
correction factors for the filter implementation. The prediction
error is utilized as a feedback control signal.
[0015] A shock level estimator 56, in one embodiment, is a Kalman
Filter based algorithm that implements a capability to be initially
loaded with measured and calibrated navigational estimates via
sensor processing block 52. The navigational estimates are based on
a recursive method for the least square estimation of coefficients
for a linear system. The recursive method predicts changes since
the last estimate and correct these changes in real-time using a
state-space model to handle the times and measurement updates of
the system dynamics. Such methods include time and measurement
updates which are utilized in determining prediction and correction
error estimates and covariance. In addition, shock level estimator
56 is configured to be periodically updated with data originating
from the sensors within the IMU. Data originating from IMU sensors
received by shock level estimator 56 includes acceleration
components (e.g., velocity and position) that have been integrated
once to provide an IMU computed velocity, and integrated twice to
provide an IMU computed position.
[0016] In one embodiment, acceleration components 57 are
representative of six dimensional state variables with respect to a
space fixed reference frame used in conjunction with a direction
cosine matrix calculated from gyroscopes within the IMU for gravity
compensation. In strap-down system mechanization, where both
gyroscopes and accelerometers of the IMU are mounted on the
vehicle/missile platform, having the sensitive axes of the
gyroscopes orthogonal to the axes of the accelerometer enables
velocity and position resolution by twice integrating the true
acceleration derived and measured from the accelerometers.
Therefore, a measure of the vehicle/missile body attitude using the
gyroscope angular rate is achieved, from which the direction cosine
matrix is determined and calculated.
[0017] Shock level estimator 56 provides estimated correction
factors 60 which are combined with the prediction errors within
feedback control signals 62 from ACTA 54 by summing component 64.
This combination enables dynamic compensation for an IMU (e.g., IMU
10) used in a strapdown inertial system mechanization. The
compensation is applicable when the missile experiences fast turn
rates and high acceleration during its flight path (i.e. navigation
errors increasing due to high acceleration and rapid turn rates and
their effects upon the IMU).
[0018] A shock level corrector 66 receives the combined estimated
correction factors 60 and the prediction errors within feedback
control signals 62 and detects errors between the two that are
related to variations in the state variables. Such errors are
detected, in one embodiment, using time and measurement update
estimates through implementation of prediction and correction
estimation algorithms. In one embodiment, these estimation
algorithms are based on Kalman filter algorithms.
[0019] Upon receipt of these state variable variations, shock level
corrector 66 is configured to compute appropriate adjustment
factors 68 based on the state variable variations which are then
input into sensor processing block 52 which calculates driving
signals 70 that are applied to a shock attenuator drive 72 which
then provides compensation signals 74 for the IMU. In one
embodiment, these adjustment factors are actual measurements that
are computed to correct projected estimates in real-time. The
adjustment factors are then conditioned by shock actuator drive 72
to provide appropriate compensation signals 74. As a result, shock
actuator drive 72 actively damps any oscillations and vibrations
associated with the detected errors through compensation signals
74.
[0020] FIG. 3 is a flow chart 100 which further illustrates the
methods performed by shock compensator control system 50 (shown in
FIG. 2). Specifically, sensor processing block receives 102
calibration and navigational data updates. Separately, shock level
estimator 56 (shown in FIG. 2) accumulates and computes 104 IMU
based vehicle attitude, velocity, and position estimates. ACTA 54
(shown in FIG. 2) accumulates and computes 106 IMU based vehicle
attitude, velocity, and position predictions.
[0021] The attitude, velocity, and position estimates are validated
108 against the calibration and navigational data updates and the
attitude, velocity, and position predictions are validated 110
against the calibration and navigational data updates. It is then
determined 112 whether the validated, estimated attitude, velocity,
and position are valid. If so, shock level estimator 56 is loaded
114, with the current estimates of attitude, velocity, and
position. It is also determined 116 whether the validated,
predicted attitude, velocity, and position are valid. If so, ACTA
54 is loaded 118, with the current predictions of attitude,
velocity, and position.
[0022] Invalid estimates and predictions of attitude, velocity, and
position and loaded 114 estimates and loaded 118 predictions are
synthesized 120 resulting in compensated 122 IMU attitude,
velocity, and position data. The compensated IMU attitude,
velocity, and position data is then utilized to provide 124 driving
signals 70 that are applied to a shock attenuator drive 72.
[0023] The filter coefficients from ACTA 54 are utilized with
estimated correction factors from shock level estimator 56 to
generate the above described adjustment factors for the state
variables. The adjustment factors are utilized to actively
compensate and damp shock and vibration within an IMU by monitoring
and adapting to changes and extracting only appropriate control
signals.
[0024] Utilization of adaptive control technique algorithm (ACTA)
54 combined with the above described dual mode feedforward and
feedback control system 50 is an integral component of an IMU, for
example IMU 10 (shown in FIG. 1) or any other system that requires
active shock and vibration disturbance rejection. In the case of an
IMU utilized in a missile, control system 50 enables in-system
dynamic compensation for the IMU when exposed to shock wave
transient conditions during the flight of the missile. The dynamic
compensation results as dual mode feedforward and feedback control
system 50 continuously performs shock level estimation and
correction, and senses acceleration, velocity and displacement,
respectively. ACTA 54, which is based on re-configurable hardware
digital filter functions, for example, finite impulse response
(FIR) functions, filters sensed acceleration, velocity and
displacement feedback signals to effectively enable shock and
vibration active damping capability for each axis of the tri-axial
accelerometers utilized in certain IMUs. The tri-axial
accelerometers within these IMUs are based on an orthogonal
configuration in such a way that acceleration, velocity and
displacement will synthesize the feedback control to dynamically
compensate for shock and vibration levels exceeding pre-defined
shock and vibration thresholds for the IMUs.
[0025] The above described methods and systems address the need for
shock and vibration disturbance rejection in missile, interceptor,
and other similar inertial guidance systems. While the invention
has been described in terms of various specific embodiments, those
skilled in the art will recognize that the invention can be
practiced with modification within the spirit and scope of the
claims.
* * * * *