On Autonomous Articulated Vehicles

180 Pages·2015·13.01 MB·English

DOCTORA L T H E S IS
Department of Computer Science, Electrical and Space Engineering
Division of Signals and Systems
On Autonomous Articulated Vehicles
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On Autonomous Articulated Vehicles
Thaker Mahmood Nayl
AutomaticControlEnginnering
DivisionofSignalsandSystems
DepartmentofComputerScience,ElectricalandSpaceEngineering
Lulea˚ UniversityofTechnology
Lulea˚,Sweden
June2015
Supervisors:
GeorgeNikolakopoulosandThomasGustafsson
Printed by Luleå University of Technology, Graphic Production 2015
ISSN 1402-1544
ISBN 978-91-7583-348-4 (print)
ISBN 978-91-7583-349-1 (pdf)
Luleå 2015
www.ltu.se
Tomyfamilyfortheirunconditional
supportthroughoutalltheseyears

A
BSTRACT
Theobjectiveofthisthesisistoaddresstheproblemsofmodeling,pathplanningandpathfollowing
foranarticulatedvehicleinarealisticenvironmentandinthepresenceofmultipleobstacles.
In greater detail, the problem of the kinematic modeling of an articulated vehicle is revisited
throughtheproposalofapropermodelinwhichthedimensionsandpropertiesofthevehiclecanbe
fullydescribed,ratherthanconsideringitasaunitpoint.Basedonthisapproach,nonlinearandlinear
errorkinematicsmodelsareproposedthatarealsoabletoaccountfortheeffectoftheslipangles,a
factorthatcancausedramaticdeteriorationintheoverallperformanceofthevehicle.
Subsequently,twodifferentconceptsforaddressingtheproblemofpathfollowingforarticulated
vehiclesareproposed.Thefirstconceptisbasedonaswitchingmodelpredictivecontrolarchitecture,
whichreliesonmultipleswitchinglinearerrordynamicsmodelsofthearticulatedvehicletoaccount
for the effect of varying the slip angles and cruising speed as well as the mechanical and physical
constraints of the vehicle. The second proposed control concept is a novel nonlinear sliding mode
controller that introduces continuous sliding surfaces to reduce chattering effects while tracking a
reference trajectory. The sliding mode controller is utilized based on the extracted nonlinear error
coordinatesofthearticulatedvehicle.Thefeasibilityofthisapproachhasbeendemonstratedthrough
multipleexperimentaltestsonasmallscaleusingafullyrealisticarticulatedvehicle.
Finally,inthepathplanningpartofthethesis,artificialpotentialfieldandbugalgorithmsaread-
dressed. Morespecifically,thepotentialfieldpathplanningalgorithmismodifiedbyconsideringthe
nonlinearkinematicmodelofthearticulatedvehicleandcorrespondinglyadaptingtherepulsiveand
attractivecoefficients. Inthecaseofthewell-knownbugalgorithm,asuitablenavigationmethodfor
anarticulatedvehicleforlocalpathplanningbasedonaminimumsetofsensorsandwithdecreased
complexityforonlineimplementationisalsoproposed.Furthermore,theperformanceofthemodified
potentialfieldmethodhasbeenexperimentallyevaluatedinmultiplepathplanningscenariosusing
thepreviouslymentionedsmall-scalerealisticarticulatedvehicle.

C
ONTENTS
PartI
1 ListofPublicationsandContributions 3
1.1 PublicationsAppendedtotheThesis . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 PublicationsNotAppendedtotheThesis. . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 SummaryofPublications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 ThesisOutline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2 Introduction 9
2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 RelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3 MathematicalModel 17
3.1 ModelingofanArticulatedVehicle. . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2 ErrorDynamicsModeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4 ControlDesign 25
4.1 SwitchingModelPredictiveControl . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.2 SlidingModeControl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5 PathPlanning 35
5.1 BugPathPlanningAlgorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.2 ModifiedPotentialFieldAlgorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . 37
6 ConclusionsandFutureWork 43
6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
6.2 FutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
References 51
PartII
PaperA 55
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
II CONTENTS
2 ArticulatedVehicleModeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3 ModelPredictiveControlDesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
PaperB 79
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
2 ArticulatedVehicleModeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
3 ErrorDynamicsModeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
4 ModelPredictiveControlDesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
5 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
PaperC 95
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
2 ArticulatedVehicleErrorDynamicsModeling . . . . . . . . . . . . . . . . . . . . . 98
3 OnLineMPCbasedPathPlanningforArticulatedVehicle . . . . . . . . . . . . . . 101
4 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
PaperD 111
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
2 ArticulatedVehicleModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
3 OnlineSmoothPathPlanningforanArticulatedVehicle . . . . . . . . . . . . . . . 116
4 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
PaperE 127
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
2 ArticulatedVehicleAndErrorDynamicModels . . . . . . . . . . . . . . . . . . . . 130
3 PathPlanningandMotionControl . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
4 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
PaperF 149
1 ArticulatedVehicleModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
2 SlidingModeControlforanArticulatedVehicle. . . . . . . . . . . . . . . . . . . . 154
3 SystemArchitecture. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
4 ExperimentalResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163