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Navigation control for autonomous tr...

Qiu, Hongchu.

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Navigation control for autonomous tractor guidance.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Navigation control for autonomous tractor guidance./
Author:	Qiu, Hongchu.
Description:	105 p.
Notes:	Adviser: Qin Zhang.
Contained By:	Dissertation Abstracts International63-11B.
Subject:	Artificial Intelligence. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3070040
ISBN:	0493899839

Navigation control for autonomous tractor guidance.
Qiu, Hongchu.

Navigation control for autonomous tractor guidance. - 105 p.

Adviser: Qin Zhang.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.

The objective of this study was to develop an intelligent tractor guidance control system capable of tracking straight pathways, curved pathways, and turns during normal farming operations. The posture sensors used here were a real time kinematic global positioning system (RTK-GPS) receiver and a fiber optic gyroscope (FOG). Models of both an electrohydraulic steering system and a vehicle dynamic system were developed. The open loop electrohydraulic steering system was found to be a “type 1” system and could be simplified as a third order transfer function to the control input signal. A proportional steering controller, along with the deadband compensation, was capable of providing adequate tracking performance for an electrohydraulic steering system. Both a linear tractor dynamic bicycle model and a geometrically nonlinear tractor dynamic bicycle model were successfully developed and were represented by the tractor sideslip angle and the yawing rate. The developed geometrically nonlinear two degrees of freedom vehicle dynamic model was found to be more accurate than a linear dynamic model for vehicle trajectory simulation. The developed models were used for computer simulation development, steering system controller design, and gain scheduling navigation controller design.

ISBN: 0493899839Subjects--Topical Terms:

769149
Artificial Intelligence.

Navigation control for autonomous tractor guidance.
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005 20110505
008 110505s2002 eng d
020 $a 0493899839
035 $a (UnM)AAI3070040
035 $a AAI3070040
040 $a UnM $c UnM
100 1 $a Qiu, Hongchu. $3 1256980
245 1 0 $a Navigation control for autonomous tractor guidance.
300 $a 105 p.
500 $a Adviser: Qin Zhang.
500 $a Source: Dissertation Abstracts International, Volume: 63-11, Section: B, page: 5355.
502 $a Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.
520 $a The objective of this study was to develop an intelligent tractor guidance control system capable of tracking straight pathways, curved pathways, and turns during normal farming operations. The posture sensors used here were a real time kinematic global positioning system (RTK-GPS) receiver and a fiber optic gyroscope (FOG). Models of both an electrohydraulic steering system and a vehicle dynamic system were developed. The open loop electrohydraulic steering system was found to be a “type 1” system and could be simplified as a third order transfer function to the control input signal. A proportional steering controller, along with the deadband compensation, was capable of providing adequate tracking performance for an electrohydraulic steering system. Both a linear tractor dynamic bicycle model and a geometrically nonlinear tractor dynamic bicycle model were successfully developed and were represented by the tractor sideslip angle and the yawing rate. The developed geometrically nonlinear two degrees of freedom vehicle dynamic model was found to be more accurate than a linear dynamic model for vehicle trajectory simulation. The developed models were used for computer simulation development, steering system controller design, and gain scheduling navigation controller design.
520 $a A supervisory preview navigation control algorithm was developed for autonomous tractor guidance. The supervisory controller consisted of a preview parameter processing module, a traveling speed controller, and a gain scheduling navigation controller. The feedforward and feedback gain scheduling navigation controller generated the steering angle signal to steer the autonomous tractor to follow desired straight and curved paths.
520 $a The validation of the developed supervisory preview navigation controller was conducted with both computer simulation and field tests on an agricultural tractor platform equipped with RTK-GPS and FOG posture sensors. The field tests showed that the root mean squared (RMS) offset error was less than 0.05 <italic> m</italic> and the maximum offset error was less than 0.1 <italic>m</italic> for a straight path at speeds of up to 3 <italic>m</italic>/<italic>s </italic>. The RMS offset error was less than 0.1 <italic>m</italic> and the maximum offset error of 0.2 <italic>m</italic> for a curved path with a radius of 0.1 <italic>m</italic> at speeds of up to 1.5 <italic>m</italic>/<italic> s</italic>.
590 $a School code: 0090.
650 4 $a Artificial Intelligence. $3 769149
650 4 $a Engineering, Agricultural. $3 1019504
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Engineering, System Science. $3 1018128
690 $a 0539
690 $a 0548
690 $a 0790
690 $a 0800
710 2 0 $a University of Illinois at Urbana-Champaign. $3 626646
773 0 $t Dissertation Abstracts International $g 63-11B.
790 $a 0090
790 1 0 $a Zhang, Qin, $e advisor
791 $a Ph.D.
792 $a 2002
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3070040