GPS control of a tractor-towed implement

Information

  • Patent Grant
  • 6434462
  • Patent Number
    6,434,462
  • Date Filed
    Thursday, June 28, 2001
    23 years ago
  • Date Issued
    Tuesday, August 13, 2002
    22 years ago
Abstract
A control system controls a work vehicle towing a towed implement. The control system includes a steering angle sensor, an implement position generating unit generating an actual implement position signal, a desired implement position generating unit generating a desired implement position signal, a vehicle position generating unit generating an actual vehicle position signal, a processor unit generating an implement angle signal as a function of the actual implement position signal and the actual vehicle position signal, and a control processor generating the steering control signal as a function of the actual implement position signal, the actual vehicle position signal, the implement angle signal, the steering angle signal and the desired implement position signal. A vehicle steering actuator steering vehicle steerable wheels in response to the control signal.
Description




FIELD OF THE INVENTION




The invention relates to a system for automatically steering a tractor in response to an implement position signal generated by global positioning system (GPS) receiver on an implement being pulled by the tractor.




BACKGROUND OF THE INVENTION




There are known control systems for controlling robotic vehicles pulling trailers. There are also known control systems for controlling heavy trailer truck combinations. However, such systems are not designed to specifically control the location of the trailer. A system is also known for controlling a tractor mounted implement, using GPS measurements, through actuation of the implement itself. However, large actuation forces are required to move large towed implements plowing soil, and in some cases the actuation moves the tractor instead of the implement.




Larsen, W. E., Nielsen, G. A., Tyler, D. A., “Precision Navigation with GPS,” in Computers and Electronics in Agriculture, Vol. 11, 1995, pp. 85-95, suggest that GPS can be used to navigate a tractor and implement along a predetermined path, and appears to describe a model which, based on the geometry of the tractor and implement, determines or calculates the position of the implement. However, in certain situation, using a model to calculate implement position can produce erroneous implement position information, such as when a tractor and an implement are operating on a hillside.




Smith, L. A., Schafer, R. L. and Young, R. E., in “Control Algorithms for Tractor-Implement Guidance,” Transactions of the ASAE, Vol. 28, No. 2, March-April 1985, pp. 415-419 describe control algorithms for guiding a tractor-implement combination. However, these algorithms are based on a “constant-turn” geometric relationship, and, in the aforesaid hillside situation, using such a geometric relationship can also produce erroneous implement position information.




U.S. Pat. No. 5,764,511, issued Jun. 9, 1998 to Henderson, discloses a system and method for controlling the slope of cut of a work implement moved across a terrain by a vehicle. However, this system does not control the steering of the vehicle.




SUMMARY OF THE INVENTION




Accordingly, it is desired to provide a control system designed to accurately control the position of an implement towed by a tractor.




A further object of the invention is to provide such a system which utilizes GPS technology.




Another object of the invention is to provide such a system which uses differential carrier-phase GPS measurements on both the tractor and towed implement.




Another object of the invention is to provide such a system wherein control is accomplished through the steering actuation of the tractor.




These and other objects are achieved by the present invention, wherein a control system is provided for a work vehicle towing a towed implement. The vehicle has a steering system including a steering actuator for steering steerable wheels. The control system includes a steering angle sensor for generating a steering angle signal representing an angular position of the steerable wheels, and an implement GPS antenna and receiver on the implement for generating implement position data. The control system also includes a fixed land-based GPS antenna and receiver for generating reference position data. A set of vehicle GPS antennas are mounted on the vehicle, and a vehicle GPS receiver is coupled to one of the vehicle GPS antennas and generates vehicle position data. A vehicle wireless receiver receives transmitted reference position data. A vector unit coupled to the vehicle GPS antennas generates a vehicle attitude signal. A first processor generates an implement position signal as a function of the implement position data and the reference position data. A second processor generates a vehicle position signal as a function of the vehicle position data and the reference position data. An inverse kinematics processor is coupled to the first and second processors and to the vector unit, and generates an implement angle signal as a function of the implement position data, the vehicle position data and the vehicle attitude signal. A control processor is coupled to the first and second processors, to the vector unit, to the an inverse kinematics processor, to the steering angle sensor, and generates a steering control signal as a function of the implement position data, the vehicle position data and the vehicle attitude signal, the implement angle signal, the steering angle signal and a stored desired implement position signal (such as a pair of east/west coordinates). The steering actuator receives the steering control signal and steers the steerable wheels in response thereto.











BRIEF DESCRIPTION OF THE DRAWINGS





FIG. 1

is a simplified schematic diagram of an implement towed by a tractor;





FIG. 2

is a simplified schematic diagram similar to

FIG. 1

, but illustrating the variables involved in calculating the implement angle θ; and





FIG. 3

is a simplified control system block diagram of the control system of the present invention.











DESCRIPTION OF THE PREFERRED EMBODIMENT




Referring to

FIGS. 1 and 2

, a tractor


10


includes steerable wheels


12


steered by an electrically actuated steering valve


13


and a drawbar


14


. The steering valve provides a steering slew rate. A towed implement


16


, has a tongue


18


which is pivotally coupled to the drawbar


14


by a tow pin


19


so that the implement


16


can be towed through a field by the tractor


10


. The implement's kinematic center of rotation (CR) as well as the implement control point (cp) are shown in FIG.


1


. The center of rotation is the point on the implement


16


where the lateral velocity is equal to zero, which is the point that the implement


16


rotates about. The tractor has position, velocity, heading, yaw, yaw rate, yaw acceleration, heading bias, steer angle, steering angle slew rate, steer angle bias, gyro bias and radar bias parameters as shown in FIG.


1


and as indicated in Table I.




Referring now to

FIG. 3

, the control system


20


includes a steering angle sensor


22


, such as a linear potentiometer, for generating a steering angle signal δ representing an angular position of the steerable wheels


12


. An implement GPS antenna


24


is mounted on the implement


16


at the control point cp. A first GPS receiver


26


is coupled to the implement GPS antenna


24


and generates implement position data. GPS receiver


26


may be mounted on either the tractor


10


or the implement


16


.




A fixed land-based GPS antenna


28


is mounted at a fixed location on the earth. A second GPS receiver


30


is coupled to the land-based GPS antenna


28


and generates reference position data. A wireless transmitter


32


, such as a commercially available radio modem, transmits the reference position data to a vehicle mounted wireless receiver


34


, also a commercially available radio modem.




A plurality of vehicle GPS antennas


36


-


42


are mounted on the tractor


10


. A third GPS receiver


44


is coupled to one of the vehicle GPS antennas


42


and generates vehicle position data. A known vector unit


46


, such as Part No. 27760-00, manufactured by Trimble Navigation Limited, is coupled to the vehicle GPS antennas


36


-


42


and generates a vehicle attitude signal including tractor yaw (ψ), roll (φ) and pitch (λ) data. For further information relating to such a vector unit and the generation of such an attitude signal, reference is made to Parkinson, B. W., and Spilker, J. J., ed.: Global Positioning System: Theory and Applications, Volume 1-2, AIAA, 1996; Cohen C. E., Parkinson, B. W., and McNally, B. D.,: Flight Tests of Attitude Determination Using GPS Compared Against an Inertial Navigation Unit, Navigation: Journal of the Institute of Navigation, Vol. 41, No. 1, Spring 1994; and to the following issued patents: U.S. Pat. No. 5,268,695, issued to Dentinger, et al. in 1993, U.S. Pat. No. 5,296,861, issued to Knight in 1994, U.S. Pat. No. 4,847,862, issued to Braisted, et al. in 1989, U.S. Pat. No. 5,548,293, issued to Cohen in 1996, and U.S. Pat. No. 5,101,356, issued to Timothy, et al. in 1992. Alternatively, yaw rate information could be provided by a sensor such as a commercially available fiber optic gyro.




A first processor


48


is coupled to GPS receiver


26


and to wireless receiver


34


and generates an implement position signal as a function of the implement position data and the reference position data. A second processor


50


is coupled to GPS receiver


44


and to wireless receiver


34


, and generates a vehicle position signal as a function of the vehicle position data and the reference position data. Processors


48


and


50


both utilize known techniques such as Carrier Phase Differential GPS (also known as RTK GPS or Kinematic DGPS), such as described in U.S. Pat. No. 5,572,218, issued to Cohen, et al. in 1996.




A tractor electronic control unit


51


includes an inverse kinematics processor


52


and a control processor


54


. The inverse kinematics processor


52


is coupled to processors


48


and


50


and to vector unit


46


, and generates an implement angle signal θ as a function of the implement position data, the vehicle position data and the vehicle attitude signal. The implement angle (θ) is calculated from inverse kinematics using known geometrical relationships, the implement position (e


I


, n


I


), the tractor position (E


T


,N


T


), tractor heading (ψ) as well as the position of the tow pin relative to the implement and tractor positions (a, L, c), as shown in FIG.


2


. Preferably, a microprocessor (not shown) interacts with the steering valve


13


and the steer angle sensor


22


and communicates with the control unit


51


via a serial communications link (not shown). The control unit


51


preferably executes control and estimation algorithms at a 5 Hz rate using an operating system such as a Lynx real time operating system. For further information relating to the inverse kinematics processor


52


, and relating to calculation of the implement angle (θ) using simple geometry, reference is hereby made to Craig, J.,


Introduction to Robotics


, Addison-Wesley, New York, USA, 1986, and to Asada, H., Slotine, J.-J.,


Robot Analysis and Control


, Wiley-Interscience, 1986. The control processor


54


generates a steering control signal, u, which is a pulse width modulated (PWM) voltage which is applied to the electrically actuated steering valve


13


of the tractor


10


.




Referring again to

FIG. 1

, the dynamics of the tractor


10


and implement


16


are described by the following equations (1-5). The tractor position dynamics are described by:








{dot over (E)}




T




=V




x


sin(ψ)










{dot over (N)}




T




=V




x


cos(ψ)  (1)






The tractor yaw dynamics are described by:







=−2ξω



n


{umlaut over (ψ)}−ω


n




2


{dot over (ψ)}+


K




R


{dot over (δ)}


K




R







  (2)






The steering dynamics are described by:










δ
¨

=



-


d
v


I
v





δ
.


+



K
v


I
v



u






(
3
)













where the control input (u) is a pulse width modulated (PWM) voltage to a electro-hydraulic valve used to steer the front wheels.




The implement angle dynamics are described by:








{dot over (e)}




I




={dot over (E)}




T


+(


b{dot over (θ)}−b{dot over (ψ)}


)cos(θ−ψ)−


a{dot over (ψ)}


cos(ψ)










{dot over (n)}




I




={dot over (N)}




T


+(


b{dot over (θ)}−b{dot over (ψ)}


)sin(θ−ψ)+


a{dot over (ψ)}


sin(ψ)  (4)






The implement angle dynamics are described by:










θ
.

=



ψ
.



[

1
+


a
b



cos


(
θ
)




]


-



v
x

b



sin


(
θ
)








(
5
)













The model dynamics in equations (1) through (5) are of the form:








{dot over (X)}=




f


(


X


)+


Bu


  (6)






In order to utilize known state space control and estimation techniques, equations (1-5) are placed in the form:








{dot over (X)}=AX+Bu












Y=CX


  (7)






First, the position of the tow pin


19


is calculated by:








e




I




=E




T




−a


sin(ψ)










n




I




=N




T




−a


cos(ψ)






Then the offset angle of the implement GPS receiver


26


is calculated. (Note: the offset angle will be zero if the GPS receiver


26


is placed along the center line of the implement


16


).






Δθ=tan


−1


(c/I.)






Then the angle between the GPS receiver


26


and tow pin


19


is calculated:







θ
1

=


tan

-
1




(



e
l

-

e
1




n
l

-

n
1



)












The above angle is in Cartesian space and is the sum of the following angles:






θ


I


ψ+180°+θ+Δθ






Finally, the above equation is arranged as follows to determine the implement angle θ:






θ=θ


I


−(


180°+ψ+Δθ).








The control processor


54


is coupled to the first and second processors


48


and


50


, to the vector unit


46


, to the inverse kinematics processor


52


and to the steering angle sensor


22


, and receives a stored desired implement position signal. Control processor


54


executes an estimation algorithm which determines the


16


states listed in Table I so that the implement


16


can be a accurately controlled. For further information relating to the control processor


54


, reference is made to O'Connor, M. L., Elkaim, G. H., Parkinson, B. W., “Carrier Phase DGPS for Closed-Loop Control of Farm and Construction Vehicles,”


Navigation: Journal of the Institute of Navigation


, Vol. 43, No. 2, Summer 1996, pp.167-278, to Bevly, D. M., Gerdes, J. C., Parkinson, B., “Yaw Dynamic Modeling for Improved High Speed Control of a Farm Tractor,”


Proceedings of the


2000


ASME IMECE


, Orlando, Fla., to Bevly, D. M., Rekow, A., and Parkinson, B.: Evaluation of a Blended Dead-Reckoning and Carrier Phase Differential GPS System for control of an Off-Road Vehicle, Proceedings of the 1999 ION-GPS Meeting, Nashville, Tenn., September 1999, and to U.S. Pat. No. 6,052,647, issued to Parkinson, et al. in 2000.




Because the dynamics equations described earlier are non-linear, they are linearized about an operating point at each time in order to place the dynamics in the form shown in equation (7). This is done by solving for the Jacobian (J) at each time step such that:








{dot over (X)}=JX+Bu


  (11)






where:






J
=

[







f
1





x
1












f
1





x
n
























f
n





x
1












f
n





x
n






]











The biases and velocity of the tractor are assumed to be constant such that:








{dot over (V)}




x




={dot over (ψ)}




bias




={dot over (g)}




bias




={dot over (r)}




bias




={dot over (δ)}




bias




={dot over (θ)}




bias


=0






The observation matrix (C) is described by:








Y




meas




=CX+ν


  (12)






where:




Y


meas


=[E


T




GPS


N


T




GPS


ψ


GPS


δ


pot


{dot over (ψ)}


gyro


V


x




radar


e


I




GPS


n


I




GPS


θ


inv













kin


]


T






ν=unknown sensor noise vector (9×1);




There are 5 sensor bias so that:




 ψ


GPS


=ψ+ψ


bias








δ


pot


=δ+δ


bias












V




X




radar




=V




X




+r




bias










{dot over (ψ)}


gyro




={dot over (ψ)}+g




bias










θ


inv













kin


=θ+θ


bias


  (13)






The estimated states are shown in Table I and the estimated state vector is:










X
^

=

[





X
^

T







X
^

I




]





(
14
)













(where {circumflex over ( )} denotes estimates).












TABLE I











Estimated States














Tractor




Implement




















X
^

T

=


[



E
^

T








N
^

T








V
^

X







ψ
^







ψ

.
^








ψ

..
^









ψ
^

b








δ

^








δ


.
^










δ

^

b








g
^

b








r
^

b


]

T




















X
^

I

=


[



e
^

1








n
^

1







θ
^








θ
^

b


]

T














E = tractor east position




e = east position







N = tractor north position




n = north position







V


X


= forward velocity




θ = angle







ψ= heading




θ


b


= angle bias







{dot over (ψ)} = yaw rate







{umlaut over (ψ)} = yaw acceleration







ψ


b


= heading bias or “crab angle”







δ = steer angle







{dot over (δ)} = steering slew rate







δ


b


= steer angle bias







g


b


= gyro bias







r


b


= radar bias















The control processor


54


also includes an Extended Kalman Filter (EKF) which includes a measurement update and time update, which is performed at each time step (k). For further information relating to Kalman Filters, reference is made to Stengel, R.,


Optimal Control and Estimation


, Dover ed, Dover Publications, Meneola, N.Y., 1994, and to Franklin, G., Powell, D., Workman, M.,


Digital Control of Dynamic Systems,


3


rd


Ed., Addison-Wesley, Menlo Park, Calif., 1998. The measurement updated is described as follows:








L




k




=P




k




C




T


(


CP




k




C




T




+R


)


−1












{circumflex over (X)}




k




={circumflex over (X)}




k




+L




k


(


y




meas




−C{circumflex over (X)}




k


)










P




k


=(


I−L




k




C


)


P




k


  (15)






where L=Kalman Gain Vector, P=State Estimation Covariance Matrix, C=Observation Matrix, R=Sensor Noise Vector, I=Identity Matrix, and {circumflex over (X)}=State Estimate Vector.




The time update is described by:








{circumflex over (X)}




k+I




={dot over (X)}




k




Δt












P




k+I




=ΦP




k




Φ




T




+Q




w


  (16)






where Φ=discretized Jacobian (J) at each time step, Q


w


=discretized process noise matrix, Δt=sample rate, and {dot over (X)} is obtained from equations (1-5). The EKF provides estimates of all the states in Table I at every time step.




The control processor


54


also includes a linear quadratic regulator (LQR) which controls the lateral error (y


I


) of the implement. Setting the control point along the center line of the implement at a distance L from the tow pin (as shown in

FIG. 1

) and assuming small heading errors and implement angle, the lateral dynamics of the implement are described by:








{dot over (y)}




I




=V




X




ψ+L{dot over (θ)}−(α




+L


){dot over (ψ)}  (17)






Linearizing equation (5) about small angles results in:










θ
.

=



(

1
+

a
b


)



ψ
.


-



V
X

b


θ






(
18
)













The remaining dynamics necessary for full state feedback control are the yaw and steering dynamics in equations (2-3). Again Equations (17-18) and Equations (2-3) must be placed into the state space form shown in equation (7) for the lateral control states (X


c


):




 {dot over (X)}


C




=A




C




X




C




+B




C




u


  (19)




where







X
C

=


[




y
l



θ


ψ



ψ
.




ψ
¨



δ



δ
.




]

T






A
C

=

[







0





-

V
X




L
I


b




V
X





a


(


L
I

-
b

)


b



0


0


0




0




-

V
X


b



0



1
+

a
/
b




0


0


0




0


0


0


1


0


0


0




0


0


0


0


1


0


0




0


0


0



-

ω
n
2






-
2



ξω
n






K
R


Z




K
R





0


0


0


0


0


0


1




0


0


0


0


0


0




-

d
V


/

I
V









]






B
C

=


[



0


0


0


0


0


0




K
V

/

I
V





]

T











The linear lateral dynamics can then be used to calculate the LQR control gains for the control law:








u=−K




comp




X




comp


  (20)






where:




X


comp


=[ŷ


I


{circumflex over (θ)} {circumflex over (ψ)}


err


{dot over ({circumflex over (ψ)})} {umlaut over ({circumflex over (ψ)})} {circumflex over (δ)} {dot over ({circumflex over (δ)})}]


T






and where the {circumflex over ( )} denotes estimates. The heading error {dot over (ψ)}


err


is simply the difference in the desired and actual heading:






{circumflex over (ψ)}


err


={circumflex over (ψ)}−ψ


des


  (27)






The lateral error of the implement, ŷ


I


, is the distance of the implement control point to the desired line and can be found by:








ŷ




I


=(


ê




I




−E




des


)cos(ψ


des


)−(


{circumflex over (n)}




I




−N




des


)sin(ψ


des


)  (28)






All other estimates come from the EKF estimation method described previously.




The LQR compensator gain vector (K


comp


) is solved at each time step (by solving the Riccati equation in real time) using the following control state weighting matrix (Q) and control input weighting value (R):












Q
=

diag


[




Q
y




Q
θ




Q
ψ




Q

ψ
.





Q

ψ
¨





Q
δ




Q

δ
.





]








=

diag


[



1


0


0


0


0


10


0



]









(
21
)













R


u


=1.0




K


comp


can be computed from Q, R


u


, A


c


, and B


c


. Methods for calculating the LQR gains for a system can be Stengel, R.,


Optimal Control and Estimation


, Dover ed, Dover Publications, Meneola, N.Y., 1994, and to Franklin, G., Powell, D., Workman, M.,


Digital Control of Dynamic Systems


, 3


rd


Ed., Addison-Wesley, Menlo Park, Calif., 1998.




The stored desired implement position signal is preferably a pair of east/west coordinates which is stored in a memory (not shown) of the tractor electronic control unit


51


, such as part of a stored path to be traversed. The control processor


54


generates a steering control signal as a function of the implement position data, the vehicle position data and the vehicle attitude signal, the implement angle signal, the steering angle signal and the stored desired implement position signal. The steering actuator


13


receives the steering control signal and steers the steerable wheels


12


in response thereto.




While the present invention has been described in conjunction with a specific embodiment, it is understood that many alternatives, modifications and variations will be apparent to those skilled in the art in light of the foregoing description. Accordingly, this invention is intended to embrace all such alternatives, modifications and variations which fall within the spirit and scope of the appended claims.



Claims
  • 1. A control system for a work vehicle towing a towed implement, the vehicle having a steering system including steering actuator for steering steerable wheels in response to a steering control signal, the control system comprising:a steering angle sensor for generating a steering angle signal representing an angular position of the steerable wheels; an implement position generating unit generating actual implement position data; an desired implement position generating unit generating a desired implement position signal; a vehicle position generating unit generating vehicle position data; a processor unit generating an implement angle signal as a function of the actual implement position data and the vehicle position data; and a control processor generating the steering control signal as a function of the actual implement position data, the vehicle position data, the implement angle signal, the steering angle signal and the desired implement position signal, the steering actuator receiving the steering control signal and steering the steerable wheels in response thereto.
  • 2. The control system of claim 1, wherein:an implement GPS antenna is mounted on the implement and a GPS receiver is coupled to the implement GPS antenna and generates the actual implement position data.
  • 3. The control system of claim 1, wherein:the vehicle position generating unit comprises a vehicle GPS antenna mounted on the work vehicle, and a vehicle GPS receiver coupled to the vehicle GPS antenna and generating the vehicle position data.
  • 4. The control system of claim 1, further comprising:a fixed land-based GPS antenna; a land-based GPS receiver coupled to the land-based GPS antenna and generating reference position data; a wireless transmitter for transmitting the reference position data; a vehicle mounted wireless receiver for receiving the reference position data from the transmitter.
  • 5. The control system of claim 4, further comprising:a plurality of vehicle GPS antennas mounted on the work vehicle; a GPS receiver coupled to one of the vehicle GPS antennas and generating the vehicle position data; a vector unit coupled to the vehicle GPS antennas and generating a vehicle attitude signal; a first processor for generating an implement position signal as a function of the implement position data and the reference position data; and a second processor for generating a vehicle position signal as a function of the vehicle position data and the reference position data.
  • 6. The control system of claim 5, further comprising:an inverse kinematics processor coupled to the first and second processors and to the vector unit, and generating an implement angle signal as a function of the implement position signal, the vehicle position signal and the vehicle attitude signal; and a control processor coupled to the first and second processors, to the vector unit, to the inverse kinematics processor, to the steering angle sensor, and generating the steering control signal as a function of the implement position signal, the vehicle position signal and the vehicle attitude signal, the implement angle signal, the steering angle signal and a stored desired implement position signal.
  • 7. A control system for a work vehicle towing a towed implement, the vehicle having a steering system including steering actuator for steering steerable wheels, the control system comprising:a steering angle sensor for generating a steering angle signal representing an angular position of the steerable wheels; an implement GPS antenna mounted on the implement; a first GPS receiver coupled to the implement GPS antenna and generating implement position data; a fixed land-based GPS antenna; a second GPS receiver coupled to the land-based GPS antenna and generating reference position data; a wireless transmitter for transmitting the reference position data; a vehicle mounted wireless receiver for receiving the reference position data from the transmitter; a plurality of vehicle GPS antennas mounted on the work vehicle; a third GPS receiver coupled to one of the vehicle GPS antennas and generating vehicle position data; a vector unit coupled to the vehicle GPS antennas and generating a vehicle attitude signal; a first processor for generating an implement position signal as a function of the implement position data and the reference position data; a second processor for generating a vehicle position signal as a function of the vehicle position data and the reference position data; an inverse kinematics processor coupled to the first and second processors and to the vector unit, and generating an implement angle signal as a function of the implement position data, the vehicle position data and the vehicle attitude signal; and a control processor coupled to the first and second processors, to the vector unit, to the an inverse kinematics processor, to the steering angle sensor, and generating a steering control signal as a function of the implement position data, the vehicle position data and the vehicle attitude signal, the implement angle signal, the steering angle signal and a stored desired implement position signal, the steering actuator receiving the steering control signal and steering the steerable wheels in response thereto.
  • 8. A control system for a work vehicle towing a towed implement, the vehicle having a steering system including steering actuator for steering steerable wheels in response to a steering control signal, the control system comprising:means for generating position data representing an actual position of the implement and an actual position of the vehicle position; means for generating desired implement position signal representing a desired position of the implement; and means for generating the steering control signal as a function of the position data and the desired implement position signal, the steering actuator receiving the steering control signal and steering the steerable wheels in response thereto so that the vehicle moves the implement to the desired position.
  • 9. The control system of claim 8, wherein the control system comprises:a steering angle sensor for generating a steering angle signal representing an angular position of the steerable wheels; means for generating an implement angle signal as a function of the position data; and means for generating the steering control signal as a function of the position data, implement angle signal, the steering angle signal and the desired implement position signal.
US Referenced Citations (10)
Number Name Date Kind
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