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E-raamat: Fault Diagnosis and Fault-Tolerant Control of Robotic and Autonomous Systems

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  • Formaat: EPUB+DRM
  • Sari: Control, Robotics and Sensors
  • Ilmumisaeg: 25-Jul-2020
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785618314
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Fault Diagnosis and Fault-Tolerant Control of Robotic and Autonomous SystemsSuurem pilt
  • Formaat: EPUB+DRM
  • Sari: Control, Robotics and Sensors
  • Ilmumisaeg: 25-Jul-2020
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785618314
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Robotic systems have experienced exponential growth thanks to their incredible adaptability. Modern robots require an increasing level of autonomy and the capability to interact with humans. This book addresses the challenges of increasing and ensuring reliability and safety of modern robotic and autonomous systems. The book provides an overview of research in this field to-date, and addresses advanced topics including fault diagnosis and fault-tolerant control, and the challenging technologies and applications in industrial robotics, robotic manipulators, mobile robots, and autonomous and semi-autonomous vehicles.

Chapters cover the following topics: fault diagnosis and fault-tolerant control of unmanned aerial vehicles; control techniques to deal with the damage of a quadrotor propeller; observer-based LPV control design of quad-TRUAV under rotor-tilt axle stuck fault; an unknown input observer based framework for fault and icing detection and accommodations in overactuated unmanned aerial vehicles; actuator fault tolerance for a WAM-V catamaran with azimuth thrusters; fault-tolerant control of a service robot; distributed fault detection and isolation strategy for a team of cooperative mobile manipulators; nonlinear optimal control for aerial robotic manipulators; fault diagnosis and fault-tolerant control techniques for aircraft Systems; fault-tolerant trajectory tracking control of in-wheel motor vehicles with energy efficient steering and torque distribution; nullspace-based input reconfiguration architecture for over-actuated aerial vehicles; data-driven approaches to fault-tolerant control of industrial robotic systems.



Robotic systems have experienced exponential growth thanks to their incredible adaptability. Modern robots require an increasing level of autonomy and the capability to interact with humans. This book addresses the challenges of increasing and ensuring reliability and safety of modern robotic and autonomous systems.

List of contributors
xiii
About the editors xxi
Foreword xxiii
1 Fault diagnosis and fault-tolerant control of unmanned aerial vehicles
1(24)
Ban Wang
Youmin Zhang
1.1 Introduction
1(4)
1.1.1 Unmanned aerial vehicle
1(1)
1.1.2 Fault detection and diagnosis
2(1)
1.1.3 Fault-tolerant control
3(2)
1.2 Modeling of an unmanned quadrotor helicopter
5(4)
1.2.1 Kinematic equations
5(2)
1.2.2 Dynamic equations
7(1)
1.2.3 Control mixing
8(1)
1.2.4 Actuator fault formulation
9(1)
1.3 Active fault-tolerant control
9(8)
1.3.1 Problem statement
10(1)
1.3.2 Adaptive sliding mode control
11(1)
1.3.3 Construction of reconfigurable mechanism
12(5)
1.4 Simulation results
17(4)
1.4.1 Fault estimation and accommodation results
18(3)
1.5 Conclusions
21(1)
References
21(4)
2 Control techniques to deal with the damage of a quadrotor propeller
25(18)
Fabio Ruggiero
Diana Serra
Vincenzo Lippiello
Bruno Siciliano
2.1 Introduction
25(1)
2.2 Problem statement
26(2)
2.3 Modeling
28(3)
2.3.1 Quadrotor
28(2)
2.3.2 Birotor
30(1)
2.4 Control design
31(5)
2.4.1 PID control scheme
32(2)
2.4.2 Backstepping control scheme
34(2)
2.5 Numerical simulations
36(2)
2.5.1 Description
36(1)
2.5.2 Case study
37(1)
2.6 Conclusion
38(1)
Acknowledgments
39(1)
References
39(4)
3 Observer-based LPV control design of quad-TRUAV under rotor-tilt axle stuck fault
43(24)
Zhong Liu
Didier Theilliol
Liying Yang
Yuqing He
Jianda Han
3.1 Introduction
44(2)
3.2 Quad-TRUAV and nonlinear modeling
46(2)
3.3 LPV control analysis
48(4)
3.3.1 Polytopic LPV representation
48(2)
3.3.2 Closed-loop analysis with observer-based LPV control
50(2)
3.4 Observer-based LPV control for the quad-TRUAV
52(5)
3.4.1 Observer-based LPV controller synthesis
52(3)
3.4.2 Inverse procedure design
55(2)
3.5 Fault-tolerant design
57(2)
3.5.1 Actuator stuck fault
57(1)
3.5.2 Degraded model method for FTC
57(2)
3.6 Numerical results
59(5)
3.6.1 Fault-free results
59(2)
3.6.2 FTC results under fault
61(3)
3.7 Conclusions
64(1)
Acknowledgments
64(1)
References
64(3)
4 An unknown input observer-based framework for fault and icing detection and accommodation in overactuated unmanned aerial vehicles
67(26)
Andrea Cristofaro
Damiano Rotondo
Tor Arne Johansen
4.1 Introduction
67(1)
4.2 Vehicle model
68(5)
4.2.1 Linearization
70(1)
4.2.2 Measured outputs
71(1)
4.2.3 Control allocation setup
71(1)
4.2.4 Wind disturbance
72(1)
4.3 Icing and fault model
73(1)
4.4 Unknown input observer framework
74(2)
4.5 Diagnosis and accommodation
76(6)
4.5.1 Detection and isolation in UAVs using UIOs
76(5)
4.5.2 Control allocation-based icing/fault accommodation
81(1)
4.6 Enhanced quasi-LPV framework
82(4)
4.6.1 Nonlinear embedding
83(1)
4.6.2 LPV unknown input observer
83(1)
4.6.3 Application to the UAV fault/icing diagnosis
84(2)
4.7 Illustrative example: the Aerosonde UAV
86(4)
References
90(3)
5 Actuator fault tolerance for a WAM-V catamaran with azimuth thrusters
93(24)
Alessandro Baldini
Riccardo Felicetti
Alessandro Freddi
Kazuhiko Hasegawa
Andrea Monteriu
Jyotsna Pandey
5.1 Introduction
93(2)
5.2 Mathematical model
95(2)
5.2.1 Dynamics
95(1)
5.2.2 Actuator faults and failures
96(1)
5.3 Control system architecture in the failure-free scenario
97(7)
5.3.1 Control law
97(2)
5.3.2 Control allocation
99(2)
5.3.3 Control policy
101(3)
5.4 Control reconfiguration in the presence of failures
104(2)
5.4.1 Failure on S azimuth thruster
105(1)
5.4.2 Blocked angle on S azimuth thruster
106(1)
5.4.3 Other cases
106(1)
5.5 Simulation results
106(7)
5.5.1 Scenario I -- fault-free actuators
108(1)
5.5.2 Scenario II -- double thruster faults
108(1)
5.5.3 Scenario III -- fault and failure on thrusters
109(1)
5.5.4 Scenario IV -- stuck and faulty thruster
110(1)
5.5.5 Discussion of results
111(2)
5.6 Conclusion
113(1)
References
113(4)
6 Fault-tolerant control of a service robot
117(26)
Alberto San Miguel
Vicenc Puig
Guillem Alenya
6.1 Introduction
117(3)
6.1.1 State of the art
118(1)
6.1.2 Objectives
119(1)
6.2 Takagi--Sugeno model
120(6)
6.2.1 Robot model
120(3)
6.2.2 Takagi--Sugeno formulation
123(3)
6.3 Control design
126(3)
6.3.1 Parallel distributed control
126(1)
6.3.2 Optimal control design
127(2)
6.4 Fault and state estimation
129(3)
6.4.1 Robust unknown input observer
129(1)
6.4.2 Fault concept and design implications
130(1)
6.4.3 Fault estimation and compensation
131(1)
6.5 Fault-tolerant scheme
132(2)
6.6 Application results
134(5)
6.6.1 Basic control structure with the Luenberger observer
135(1)
6.6.2 Basic control structure with RUIO
136(1)
6.6.3 Complete fault-tolerant control scheme
137(2)
6.7 Conclusions
139(1)
Acknowledgement
140(1)
References
140(3)
7 Distributed fault detection and isolation strategy for a team of cooperative mobile manipulators
143(24)
Giuseppe Gillini
Martina Lippi
Filippo Arrichiello
Alessandro Marino
Francesco Pierri
7.1 Introduction
143(3)
7.2 Mathematical background and problem setting
146(2)
7.2.1 Robot modeling
146(1)
7.2.2 Communication
147(1)
7.2.3 Problem description
148(1)
7.3 Observer and controller scheme
148(6)
7.3.1 Collective state estimation
150(1)
7.3.2 Observer convergence
151(3)
7.4 Fault diagnosis and isolation scheme
154(4)
7.4.1 Residuals in the absence of faults
155(1)
7.4.2 Residuals in the presence of faults
156(1)
7.4.3 Detection and isolation strategy
157(1)
7.5 Experiments
158(4)
7.6 Conclusions
162(1)
Acknowledgments
163(1)
References
164(3)
8 Nonlinear optimal control for aerial robotic manipulators
167(30)
Gerasimos Rigatos
Masoud Abbaszadeh
Patrice Wira
8.1 Introduction
167(2)
8.2 Dynamic model of the aerial robotic manipulator
169(6)
8.3 Approximate linearization of the model of the aerial robotic manipulator
175(4)
8.4 Differential flatness properties of the aerial robotic manipulator
179(1)
8.5 The nonlinear H-infinity control
180(2)
8.5.1 Tracking error dynamics
180(1)
8.5.2 Min--max control and disturbance rejection
181(1)
8.6 Lyapunov stability analysis
182(3)
8.7 Robust state estimation with the use of the H-infinity Kalman filter
185(1)
8.8 Simulation tests
185(7)
8.9 Conclusions
192(1)
References
193(4)
9 Fault diagnosis and fault-tolerant control techniques for aircraft systems
197(16)
Paolo Castaldi
Nicola Mimmo
Silvio Simani
9.1 Introduction
197(2)
9.2 Aircraft model simulator
199(3)
9.3 Active fault-tolerant control system design
202(5)
9.3.1 Fault diagnosis module
203(4)
9.3.2 Fault accommodation strategy
207(1)
9.4 Simulation results
207(4)
9.4.1 Fault diagnosis filter design
208(1)
9.4.2 NLGA-AF simulation results
209(1)
9.4.3 AFTCS performance
210(1)
9.5 Conclusion
211(1)
References
211(2)
10 Fault-tolerant trajectory tracking control of in-wheel motor vehicles with energy-efficient steering and torque distribution
213(22)
Peter Gaspar
Andras Mihaly
Hakan Basargan
10.1 Trajectory-tracking controller design
214(4)
10.1.1 Vehicle modeling
214(2)
10.1.2 Reconfigurable LPV controller design
216(2)
10.2 Fault-tolerant and energy optimal control synthesis
218(7)
10.2.1 Control architecture
218(1)
10.2.2 Fault-tolerant reconfiguration
219(1)
10.2.3 Energy optimal reconfiguration
220(3)
10.2.4 Efficient wheel torque distribution
223(2)
10.3 Electric motor and battery model
225(2)
10.3.1 Lithium-ion battery
225(1)
10.3.2 Battery pack
226(1)
10.3.3 Motor model
226(1)
10.4 Simulation results
227(5)
10.5 Conclusion
232(1)
References
232(3)
11 Nullspace-based input reconfiguration architecture for over-actuated aerial vehicles
235(22)
Tamas Peni
Balint Vanek
Gyorgy Liptak
Zoltan Szabo
Jozsef Bokor
11.1 Inversion-based nullspace computation for parameter-varying systems
236(5)
11.1.1 Nullspace of a linear map
236(1)
11.1.2 Memoryless matrices
237(2)
11.1.3 LPV systems
239(2)
11.2 Geometry-based nullspace construction
241(4)
11.2.1 Parameter-varying invariant subspaces
242(1)
11.2.2 Nullspace construction for LPV systems
243(2)
11.3 Control input reconfiguration architecture for compensating actuator failures
245(2)
11.4 Reconfigurable fault-tolerant control of the B-1 aircraft
247(6)
11.4.1 The non-linear flight simulator
247(2)
11.4.2 Construction of the LPV model
249(1)
11.4.3 Actuator inversion and nullspace computation
249(1)
11.4.4 Fault signal tracking
250(1)
11.4.5 Simulation results
251(2)
11.4.6 Robustness analysis
253(1)
11.5 Conclusion
253(1)
Acknowledgements
254(1)
References
254(3)
12 Data-driven approaches to fault-tolerant control of industrial robotic systems
257(28)
Yuchen Jiang
Shen Yin
12.1 Background
257(1)
12.2 Introduction and motivation
258(2)
12.3 Data-driven control framework based on Youla parameterization
260(5)
12.3.1 System description and preliminaries
260(2)
12.3.2 Youla parameterization of all stabilizing controllers
262(2)
12.3.3 Plug-and-play control framework
264(1)
12.4 Reinforcement learning-aided approach to fault-tolerant controller design
265(6)
12.4.1 Applying RL to control system design
266(1)
12.4.2 Reward function design
266(3)
12.4.3 RL-based solution to Youla parameterization matrix
269(2)
12.5 Simulation study
271(5)
12.5.1 Simulation setup
271(1)
12.5.2 Results and discussion
272(4)
12.6 Open questions about the framework and future work
276(1)
Appendix A
277(2)
References
279(6)
13 Conclusions
285(4)
Andrea Monteriu
Alessandro Freddi
Sauro Longhi
Index 289
Andrea Monteriù is an associate professor at Università Politecnica delle Marche (Ancona, Italy). His main research interests include fault diagnosis, fault-tolerant control, nonlinear, dynamics and control, periodic and stochastic system control, applied in different fields including aerospace, marine and robotic systems. He published more than 130 papers in international journals and conferences and is involved both in national and international research projects. He is the author of the book Fault Detection and Isolation for Multi-Sensor Navigation Systems: Model-Based Methods and Applications; and a co-editor or author of four books on Ambient Assisted Living including the IET book entitled Human Monitoring, Smart Health and Assisted Living: Techniques and Technologies.



Alessandro Freddi is an assistant professor at Università Politecnica delle Marche (Ancona, Italy), where he teaches 'Preventive Maintenance for Robotics and Smart Automation' and is a founder member of 'Syncode', a startup operating in the field of industrial automation. His main research activities cover fault diagnosis and fault-tolerant control with applications to robotics, and development and application of assistive technologies. He published more than 70 papers in international journals and conferences and is involved both in national and international research projects.



Sauro Longhi is a full professor at Università Politecnica delle Marche (Ancona, Italy), where he acted as a Rector from 2013 to 2019. Since May 2014 he has been the president of the GARR Consortium, the Italian national computer network for universities and research. Since September 2019 he has also been the president of SIDRA, the Italian Society of Researchers and Professors of Automation. His research interests include modelling, identification and control of linear and nonlinear systems, control of mobile robots, underwater vehicles, vessels and unmanned aerial vehicle, cooperative control of autonomous agents, service robots for assistive applications supporting mobility and cognitive actions, home and building automation, web technology in process control and remote control laboratories, decentralized control over networks, sensors networks, power management in hybrid cars, electric motor control, embedded control system, management and control of renewable energy resources, efficient management of energy systems, automatic fault detection and isolation. He has published more than 400 papers on international journals and conferences.
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