load allocation for optimal risk management in systems with incipient failure modes

147 Pages·2013·9.82 MB·English

LOAD ALLOCATION FOR OPTIMAL RISK MANAGEMENT IN
SYSTEMS WITH INCIPIENT FAILURE MODES
APh.DDissertation
Presentedto
TheAcademicFaculty
by
BrianM.Bole
InPartialFulfillment
oftheRequirementsfortheDegree
DoctorofPhilosophyinthe
ElectricalandComputerEngineering
GeorgiaInstituteofTechnology
December2013
Copyright(cid:13)c 2013 byBrianM.Bole
LOAD ALLOCATION FOR OPTIMAL RISK MANAGEMENT IN
SYSTEMS WITH INCIPIENT FAILURE MODES
Approvedby:
DrDavidG.Taylor DrThomasGHabetler
School of Electrical and Computer Dept. ofECE
Engineering GeorgiaInstituteofTechnology
GeorgiaInstituteofTechnology
DrKaiGoebel
DrGeorgeVachtsevanos,Advisor Director of NASA Ames Prognostics
School of Electrical and Computer CenterofExcellence
Engineering NASAAmesResearchCenter
GeorgiaInstituteofTechnology
DrThomasEMichaels
Dept. ofECE DateApproved: 11/14/2013
GeorgiaInstituteofTechnology
Workhard,dreambig,andfailoften
ACKNOWLEDGEMENTS
This work has been supported by multiple grants and collaborations with public and pri-
vate organizations. The graduate funding and guidance provided by Dr. George Vachtse-
vanosandtheIntelligentControlSystemsLaboratory(ISCL)atGeorgiaTechisgratefully
acknowledged. The funding and project support provided by the United States National
AeronauticsandSpaceAdministration(NASA)undertheGraduateStudentResearchPro-
gram (GSRP) was also a huge boon to this research effort. Thank you to Dr. Kai Goebel
andthePrognosticsCenterofExcellenceatNASAAmesforthesupportandguidancepro-
videdduringmytwoyearsasaNASAGSRPfellow. TheprojectsupportbyAvSafe/SSAT
andOCT/ACLOarealsorespectfullyacknowledged.
iv
TABLE OF CONTENTS
ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
LISTOFTABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
LISTOFFIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x
SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
CHAPTERI:INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 AMotivatingDiscussionofthePrognostics-BasedDecisionMakingChal-
lenge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 IdentifiedContributionsoftheResearchEffort . . . . . . . . . . . . . . . 6
1.2.1 Claim #1 - Description of Prognostics-Based Risk Management
UsingaRetrofitNominalLoadModificationArchitecture . . . . . . 6
1.2.2 Claim #2 - Analysis of Supervisory Health Management Using Fi-
niteHorizonPrognosticEstimates . . . . . . . . . . . . . . . . . . 6
1.2.3 Claim #3 - Demonstration of the Explicit Incorporation of Future
DemandModelsintoHealthManagementPolicies . . . . . . . . . 7
1.2.4 Claim #4 - Real-World Demonstration of Stochastic Component
Health Depletion Modeling in terms of Uncertain Future Demand
Estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.3 OrganizationoftheDissertation . . . . . . . . . . . . . . . . . . . . . . . 8
CHAPTERII:BACKGROUND . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1 OriginandHistoryoftheProblem . . . . . . . . . . . . . . . . . . . . . . 9
2.1.1 FaultRiskQuantificationUsingHistoricalData . . . . . . . . . . . 9
2.1.2 ConditionBasedMaintenanceandControl . . . . . . . . . . . . . 10
2.1.3 Prognostics-BasedHealthManagement . . . . . . . . . . . . . . . 11
2.2 UncertaintyRepresentationinPrognostics . . . . . . . . . . . . . . . . . . 12
2.3 RiskQuantification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.4 ComponentLoadAllocationforRiskManagement . . . . . . . . . . . . . 16
v
CHAPTERIII:AMODULARMETHODOLOGYFORFAULTRISKASSESS-
MENTANDMANAGEMENT . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.2 AComponentLoadAllocationControlStructure . . . . . . . . . . . . . . 17
3.2.1 TheNominalControlLoop . . . . . . . . . . . . . . . . . . . . . . 17
3.2.2 ComponentLoadAllocation . . . . . . . . . . . . . . . . . . . . . 18
3.2.3 LowLevelComponentLoadAllocation . . . . . . . . . . . . . . . 21
3.3 StochasticModelingofFaultGrowthintermsofComponentLoadandNet
OutputControlEffortAllocations . . . . . . . . . . . . . . . . . . . . . . 22
3.3.1 PerformanceConstraints . . . . . . . . . . . . . . . . . . . . . . . 25
3.3.2 PrognosticConstraints . . . . . . . . . . . . . . . . . . . . . . . . 26
3.3.3 VerifyingtheFeasibilityoftheConstrainedLoadAllocationProblem 28
3.3.4 Strategic Definition of Performance Objectives and Risk Aversion
Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
CHAPTERIV:ANEXPLORATIONOFLOADALLOCATIONAMONGSIM-
ILARDEGRADINGCOMPONENTS . . . . . . . . . . . . . . . . . . . . . . 31
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.2 AFaultGrowthModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.3 AThermalModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.4 ApplicationExample-ATriplexRedundantElectromechanicalActuator . . 35
4.4.1 MechanicalDynamicsModel . . . . . . . . . . . . . . . . . . . . . 36
4.4.2 PerformanceandPrognosticsBasedLoadAllocationConstraints . . 37
4.4.3 QuantificationofPerformanceandRiskMetrics . . . . . . . . . . . 39
4.4.4 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . 40
4.5 ApplicationExample-ASkid-SteeredVehicle . . . . . . . . . . . . . . . . 49
4.5.1 MechanicalDynamicsModel . . . . . . . . . . . . . . . . . . . . . 49
4.5.2 PerformanceandPrognosticsBasedLoadAllocationConstraints . 51
4.5.3 QuantificationofPerformanceandRiskMetrics . . . . . . . . . . 53
4.5.4 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . 55
vi
CHAPTERV:AGENERALIZEDMDPFORMULATIONOFPROGNOSTIC
MODELINGANDRISKBASEDDECISIONMAKING . . . . . . . . . . . 64
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
5.2 MarkovProcessModelingofFaultGrowthDynamics . . . . . . . . . . . 65
5.2.1 IncorporatingaStochasticProcessModelforEnvironmentalLoad-
ingDemand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.3 EncodingRiskAversionintoaMarkovDecisionProcess . . . . . . . . . . 68
5.3.1 Identification of Optimal Finite Horizon Control Policies with Dy-
namicProgramming . . . . . . . . . . . . . . . . . . . . . . . . . 69
5.4 ConsiderationofaMulti-VariableStochasticSystemExample . . . . . . . 70
5.4.1 SimulationResults . . . . . . . . . . . . . . . . . . . . . . . . . . 72
5.5 SummarizingRemarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
CHAPTERVI:SIL/HILREPLICATIONOFPOWERTRAINLOADDYNAM-
ICSANDONLINEPROGNOSTICSFORAUAVAPPLICATION . . . . . . 77
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.2 AGeneralSoftware-in-the-Loop/Hardware-in-the-LoopFramework . . . . 79
6.2.1 DescriptionofInner-LoopControlDynamics . . . . . . . . . . . . 80
6.2.2 DescriptionofOuter-loopFailurePrognosticsandDecisionMaking 84
6.3 ApplicationExample-BatteryDepletionModelingonanEdge540TUAV 84
6.3.1 Edge540TInner-LoopControls . . . . . . . . . . . . . . . . . . . 86
6.3.2 BatteryDemandModeling . . . . . . . . . . . . . . . . . . . . . . 87
6.3.3 AnEquivalentCircuitBatteryModel . . . . . . . . . . . . . . . . . 92
6.3.4 BatteryChargeDepletionModeling . . . . . . . . . . . . . . . . . 95
6.3.5 PrognosticPrediction . . . . . . . . . . . . . . . . . . . . . . . . . 99
6.3.6 OnlineControlsTesting . . . . . . . . . . . . . . . . . . . . . . . . 104
6.3.7 BoundedLoadAllocation . . . . . . . . . . . . . . . . . . . . . . 108
CHAPTERVII:CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . 110
vii
APPENDIXA:RESOLVINGACTIVEREDUNDANCIESINTHELOADAL-
LOCATIONPROBLEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
APPENDIXB:THERMALMODELINGFORDCMOTORWINDINGINSU-
LATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
APPENDIX C: TRIPLEX REDUNDANT ELECTROMECHANICAL ACTU-
ATORMODELINGINFORMATION . . . . . . . . . . . . . . . . . . . . . . 117
APPENDIXD:SKID-STEEREDVEHICLEMODELINGINFORMATION . . 119
APPENDIX E: DETAILED DESCRIPTION OF AN EDGE 540T SAMPLE
FLIGHT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
VITA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
viii
LIST OF TABLES
Tables4.1: Parameter definitions for the EMA motor winding temperature dy-
namicsmodel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Tables4.2: Parameterdefinitionsfortheskid-steeredvehiclemodel . . . . . . . 52
Tables4.3: Parameterdefinitionsfortheskid-steeredvehiclemotorwindingtem-
peraturedynamicsmodel . . . . . . . . . . . . . . . . . . . . . . . 55
Tables4.4: Outcomeevaluationcostsand98%confidenceVaRestimatesformo-
tor state of health at end of mission, using three sample control rou-
tines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Tables5.1: Statistics of the accumulated state transition costs computed over re-
peatedsimulationsoffoursamplecontrolpolicies . . . . . . . . . . . 75
Tables6.1: Symbol definitions for the software-in-the-loop / hardware-in-the-
looptestingframework . . . . . . . . . . . . . . . . . . . . . . . . . 80
Tables6.2: Parameterdefinitionsfortheequivalentcircuitbatterymodel . . . . . 95
TablesC.1: Parameterdefinitionsfortheelectromechanicalactuatormodel . . . . 118
TablesD.1: Parameterdefinitionsfortheskid-steeredvehiclemodel . . . . . . . 121
ix
LIST OF FIGURES
Figure1.1: A block diagram representation for outer-loop prognostics and risk-
baseddecisionmaking . . . . . . . . . . . . . . . . . . . . . . . . . 2
Figure1.2: Measured (top) and predicted (bottom) distributions for the system
failuretimecorrespondingtotwopotentialcontrolpolicies . . . . . . 5
Figure3.1: Blockdiagramshowingtheassumedstructureofnominallycontrolled
systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Figure3.2: A functional breakdown of control tasks in the proposed component
loadallocationframework . . . . . . . . . . . . . . . . . . . . . . . 19
Figure3.3: Ablockdiagramofcomponentloadassignmentandinversionofem-
beddedcontrollogic . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Figure3.4: Areducedordersystemmodelobtainedusingtheassumptions: u =
i
r +δ and |u −r˜|≤ε . . . . . . . . . . . . . . . . . . . . . . . . . 22
i i i i
Figure3.5: AdiscreteMarkovprocessrepresentationoffaultgrowthmodeling . 23
Figure3.6: Evaluation of the prognostic constraint at several finite horizons for
twosamplecomponentloadingprofilesdenoted‘High’and‘Low’ . . 27
Figure4.1: Photograph and illustration of mechanical coupling in a triplex re-
dundantelectromechanicalactuator . . . . . . . . . . . . . . . . . . 32
Figure4.2: Anillustrationofaskid-steeredvehicle . . . . . . . . . . . . . . . . 32
Figure4.3: Additionofuncertaintytotheinsulationbreakdownmodel . . . . . . 34
Figure4.4: Anequivalentcircuitmodelformotorwindingtemperaturedynamics 35
Figure4.5: Illustration of the feasible load allocation domain for EMA motors
undertheperformanceconstraint0.8·T ≤T ≤T . . . . . . . . . . 38
c o c
Figure4.6: Illustrations of finite horizon prognostic constraint evaluation using
linear(a)andpiecewiselinear(b)interpolationfromastateofhealth
atendofmissionconstraint . . . . . . . . . . . . . . . . . . . . . . . 39
Figure4.7: AsampleEMAheadspeedprofilecommand . . . . . . . . . . . . . 40
Figure4.8: SimulationresultsforanEMAundernominalcontrol . . . . . . . . 43
Figure4.9: Simulation results for an EMA following the minimum allowable
performancepath . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
x