《Safety and Reliability in Cooperating Unmanned Aerial Systems》
《Safety and Reliability in Cooperating Unmanned Aerial Systems》协同无人机系统安全性与可靠性
作者：
Camille Alain Rabbath
Nicolas Léchevin
Defence R&D Canada - Valcartier
出版社：World Scientific
出版时间：2010年
目录
Preface v
1. Introduction 1
1.1 Unmanned Aerial Systems . . . . . . . . . . . . . . . . . . 2
1.2 Cooperative Control . . . . . . . . . . . . . . . . . . . . . 3
1.3 Contingencies . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3.1 Faults and failures of UAV components . . . . . . 7
1.3.2 Vehicle damage . . . . . . . . . . . . . . . . . . . 8
1.3.3 Information
ow faults . . . . . . . . . . . . . . . 8
1.3.4 Team anomalies and collisions . . . . . . . . . . . 9
1.3.5 Environmental e ects . . . . . . . . . . . . . . . . 10
1.3.6 Book overview . . . . . . . . . . . . . . . . . . . . 11
2. Health Management for the Individual Vehicle: A Review 13
2.1 Passive and Active Fault-Tolerant Control Systems . . . . 14
2.2 Fault/Failure Detection and Diagnosis . . . . . . . . . . . 16
2.3 Control Recon guration . . . . . . . . . . . . . . . . . . . 17
2.4 FTC and FDD Techniques for MAV and SUAV . . . . . . 19
3. Health Monitoring and Adaptation for UAS Formations 21
3.1 Models of Vehicle Dynamics, Flight Control, and Faults . 25
3.1.1 ALTAV dynamics and control . . . . . . . . . . . 26
3.1.2 Quadrotor dynamics and control . . . . . . . . . . 29
3.1.3 Actuator faults . . . . . . . . . . . . . . . . . . . . 31
3.2 Formation Control . . . . . . . . . . . . . . . . . . . . . . 33
3.2.1 Elements of contraction theory . . . . . . . . . . . 35
vii
viii Safety and Reliability in Cooperating Unmanned Aerial Systems
3.2.2 Simpli ed modeling for the purpose of formation
control synthesis . . . . . . . . . . . . . . . . . . . 37
3.2.3 Formation control objective . . . . . . . . . . . . 42
3.2.4 Closed-loop representation of the formation . . . . 43
3.2.5 Convergence analysis of state trajectories . . . . . 48
3.2.6 Modeling a formation of UAVs with realistic
nonlinear dynamics . . . . . . . . . . . . . . . . . 57
3.2.7 Trajectory of the leader and obstacle/threat
avoidance . . . . . . . . . . . . . . . . . . . . . . . 58
3.2.8 Formation control design algorithm . . . . . . . . 60
3.3 Observer-Based Decentralized Abrupt Fault Detector . . . 61
3.3.1 Context . . . . . . . . . . . . . . . . . . . . . . . . 61
3.3.2 Simpli ed model of vehicle closed-loop dynamics . 62
3.3.3 Concept of observer with disturbance attenuation 65
3.3.4 Synthesis of DAFD . . . . . . . . . . . . . . . . . 69
3.3.5 Threshold selection . . . . . . . . . . . . . . . . . 77
3.3.6 DAFD design algorithm . . . . . . . . . . . . . . . 79
3.4 Signal-Based Decentralized Non-Abrupt Fault Detector . 80
3.4.1 Context . . . . . . . . . . . . . . . . . . . . . . . . 80
3.4.2 Networked information and coupling e ects . . . . 81
3.4.3 Estimator of heading angle . . . . . . . . . . . . . 85
3.4.4 Statistical test for DNaFD . . . . . . . . . . . . . 86
3.4.5 DNaFD design algorithm . . . . . . . . . . . . . . 89
3.5 UAV Command Adaptation . . . . . . . . . . . . . . . . . 90
3.6 Simulations and Experiments . . . . . . . . . . . . . . . . 93
3.6.1 Formation control of unicycles . . . . . . . . . . . 94
3.6.2 Formation control of quadrotor aircraft . . . . . . 102
3.6.3 DAFD and formation control of ALTAVs . . . . . 104
3.6.4 DAFD and quadrotor formation control . . . . . . 112
3.6.5 DNaFD and formation control of ALTAVs . . . . 115
3.6.6 Decentralized fault detection for mixed-type,
concurrent actuator faults . . . . . . . . . . . . . 123
3.6.7 DAFD/DNaFD in closed loop with individual
vehicle FDD system . . . . . . . . . . . . . . . . . 126
3.6.8 A note on the digital implementation . . . . . . . 129
4. Decision Making and Health Management for
Cooperating UAS 131
4.1 Coordinated Rendezvous of UAS Formations . . . . . . . 134
Contents ix
4.1.1 Context . . . . . . . . . . . . . . . . . . . . . . . . 134
4.1.2 Related work . . . . . . . . . . . . . . . . . . . . . 137
4.1.3 Multi-formations . . . . . . . . . . . . . . . . . . . 138
4.1.4 Models . . . . . . . . . . . . . . . . . . . . . . . . 140
4.1.5 UAS-threat encounters modeled as Markov
decision processes . . . . . . . . . . . . . . . . . . 152
4.1.6 Problem formulation . . . . . . . . . . . . . . . . 156
4.1.7 Decision policies: perfect information . . . . . . . 160
4.1.8 Decision policies: partially known environment . . 164
4.1.9 Design of CHM and decision making system . . . 173
4.2 Cooperation Despite Information Flow Faults . . . . . . . 174
4.2.1 Context . . . . . . . . . . . . . . . . . . . . . . . . 174
4.2.2 Impact of information
ow fault on UAS decision
policies . . . . . . . . . . . . . . . . . . . . . . . . 175
4.2.3 Health state estimation . . . . . . . . . . . . . . . 177
4.2.4 Distributed computations of fW0
k;Pi;
E;j . . . . . 182
4.3 Numerical Simulations . . . . . . . . . . . . . . . . . . . . 184
4.3.1 Single target area and perfectly known
environment . . . . . . . . . . . . . . . . . . . . . 184
4.3.2 Sequence of targets and perfect knowledge of
environment . . . . . . . . . . . . . . . . . . . . . 191
4.3.3 The case of perturbed MDPs . . . . . . . . . . . . 193
4.3.4 Successive zones of surveillance in partially known
environment . . . . . . . . . . . . . . . . . . . . . 197
4.3.5 Information
ow faults . . . . . . . . . . . . . . . 199
4.4 Distributed and Parallel Implementation of Optimization
Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . 200
4.4.1 Context . . . . . . . . . . . . . . . . . . . . . . . . 200
4.4.2 Architecture . . . . . . . . . . . . . . . . . . . . . 201
4.4.3 Distributed and parallel simulation environment . 202
4.4.4 Experiments . . . . . . . . . . . . . . . . . . . . . 204
Bibliography 207
Index 221
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