Underwater Robots - Gianluca Antonelli.pdf

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262 References 253. Sarpkaya T. and Isaacson M. (1981) Mechanics of Wave Forces on Offshore Structures, VanNostrand Reinhold Co., New York, New York 254. Sciavicco L. and Siciliano B. (2000) Modeling and Control of Robot Manipulators. Springer-Verlag, London, United Kingdom 255. Schjølberg I. and Fossen T.I. (1994) Modelling and Control of Underwater Vehicle-Manipulator Systems. In: 3 rd Conference on Marine Craft Manoeuvring and Control, Southampton, United Kingdom, 45–57 256. Schjølberg I. (1996) Modeling and Control of Underwater Robotic Systems, PhD thesis for the Doktor ingeniør degree, Norwegian University ofScience and Technology, Trondheim, Norway 257. Schubak G.E. and Scott D.S. (1995) ATechno-Economic Comparison of Power Systems for Autonomous Underwater Vehicles. IEEE Journal Oceanic Engineering, 20:94–100 258. Schultz A.C. (1992) Adaptive Testing of Controllers for Autonomous Vehicles. In: Proceedings Symposium on Autonomous Underwater Vehicle Technology, Washington, DC, 158–164 259. Serrani A. (1997) Modellistica, Simulazione eControllo Nonlineare di Veicoli Sottomarini (in Italian), Dottorato di Ricerca in Sistemi Artificiali, Università degli Studi di Ancona, Ancona, Italy, 1997 260. Serrani A. and Zanoli S.M. (1998) Designing Guidance and Control Schemes for AUVs Using an Integrated Simulation Environment. In: IEEE International Conference on Robotics and Automation, Leuven, Belgium, 1079–1083 261. Shepperd S. W. (1978) Quaternion from Rotation Matrix. Journal of Guidance and Control, 1:223–224 262. Siciliano B. (1990) Kinematic Control of Redundant Robot Manipulators: A Tutorial. Journal of Intelligent Robotic Systems, 3:201–212 263. Siciliano B. and Slotine J.J. (1991), AGeneral Framework for Managing Multiple Tasks in Highly Redundant Robotic Systems, In: International Conference on Advanced Robotics, Pisa, Italy, 1211–1216 264. Slotine J.J. (1984) Sliding Controller Design for Non-Linear Systems. International Journal of Control, 40:421–434 265. Slotine J.J. and Benedetto M.D.D. (1990) Hamiltonian Adaptive Control of Spacecraft. IEEE Transactions on Automatic Control, 35:848–852 266. Slotine J.J. and Li W. (1987) Adaptive Strategies in Constrained Manipulation. In: IEEE International Conference on Robotics and Automation, Raleigh, NC, 595–601 267. Slotine J.J. and Li W. (1987) On the AdaptiveControl of Robot Manipulators. International Journal of Robotics Research, 6:49–59 268. Slotine J.J. and Li W. (1991) Applied Nonlinear Control, Prentice-Hall International Editions, USA 269. Smallwood D.A. and Whitcomb L.L. (2001) Toward Model Based Dynamic Positioning of Underwater Robotic Vehicles. In: MTS/IEEE Techno-Ocean ’01, 1106–1114 270. Smallwood D.A. and Whitcomb L.L. (2002) The Effect of Model Accuracy and Thruster Saturation on Tracking Performance of Model Based Controllers for Underwater Robotic Vehicles: Experimental Results. In: IEEE International Conference on Robotics and Automation, Washington, DC, 1081–1087 271. Smallwood D.A. and Whitcomb L.L. (2003) Adaptive Identification of Dynamically Positioned Underwater Robotic Vehicles. IEEE Transactions on Control System Technology, 11(4):505–515 272. SNAME, The Society ofNaval Architects and Marine Engineers (1950) Nomenclature for Treating the Motion of aSubmerged Body Through aFluid. In: Technical and Research Bulletin, 1–5
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Springer Tracts in Advanced Robotic
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Gianluca Antonelli Underwater Robot
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Editorial Advisory Board EUROPE Her
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Elalocomotiva sembrava fosse un mos
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Acknowledgements The contributions
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Preface to the Second Edition The p
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XVIII Preface to the First Edition
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XX Preface tothe First Edition mani
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XXII Notation η q =[η T 1 ε T η
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XXIV Notation ˜x error variable de
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XXVI Contents 3. Dynamic Control of
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XXVIIIContents A. Mathematical mode
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2 1. Introduction Maybe the first i
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4 1. Introduction (Massachusetts, U
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6 1. Introduction Fig. 1.4. Coordin
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8 1. Introduction Fig. 1.5. Pig, ma
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10 1. Introduction An example of cr
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12 1. Introduction Fig. 1.8. Romeo
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2. Modelling ofUnderwater Robots
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2.2 Rigid Body’s Kinematics 17 Th
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J T k,oqJ k,oq = 1 4 I 3 , that all
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5. compute the quaternion Q by the
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2.3 Rigid Body’s Dynamics 23 Let
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2.4 Hydrodynamic Effects 25 τ 1 =
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C A ( ν )=− C T A ( ν ) ∀ ν
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2.4 Hydrodynamic Effects 29 effects
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2.5 Gravity and Buoyancy 2.5 Gravit
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2.6 Thrusters’ Dynamics 33 Fig. 2
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2.7 Underwater Vehicles’ Dynamics
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y z 2.8 Kinematics of Manipulators
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2.9 Dynamics ofUnderwater Vehicle-M
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2.9 Dynamics ofUnderwater Vehicle-M
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2.11 Identification 43 f e = K ( x
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3. Dynamic Control of 6-DOF AUVs 3.
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3.2 Earth-Fixed-Frame-Based, Model-
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o x z o b z b x b 3.3 Earth-Fixed-F
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3.4 Vehicle-Fixed-Frame-Based, Mode
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o o b y x y b x b 3.5 Model-Based C
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3.6 Mixed Earth/Vehicle-Fixed-Frame
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3.7 Jacobian-Transpose-Based Contro
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3.8 Comparison Among Controllers 59
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3.9 Numerical Comparison Among the
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force [N] moment [Nm] 20 10 0 −10
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80 4. Fault Detection/Tolerance Str
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5. Experiments of Dynamic Control o
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5.3 Experiments of Dynamic Control
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[m] [m] 5 4 3 2 1 0 0 100 200 300 4
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5.3 Experiments of Dynamic Control
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5.4 Experiments of Fault Tolerance
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[deg] 120 100 80 60 40 20 0 −20 5
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6. Kinematic Control of UVMSs “.
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6.2 Kinematic Control 107 UVMS. Thi
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6.2 Kinematic Control 109 singulari
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6.2 Kinematic Control 111 case of t
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6.5 Singularity-Robust Task Priorit
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6.6 Fuzzy Inverse Kinematics 121 It
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Simulations 6.6 Fuzzy Inverse Kinem
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6.6 Fuzzy Inverse Kinematics 125 Fi
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vehicle attitude [deg] 20 10 0 −1
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6.6 Fuzzy Inverse Kinematics 129 It
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[-] 1 0.8 0.6 0.4 0.2 0 close 0 20
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joint positions 1-3 [deg] joint pos
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e.e. position error [m] 0.02 0.01 0
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7. Dynamic Control of UVMSs 7.1 Int
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7.2 Feedforward Decoupling Control
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7.2 Feedforward Decoupling Control
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7.4 Nonlinear Control for UVMSs wit
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7.5 Non-regressor-Based Adaptive Co
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7.6 Sliding Mode Control 7.6 Slidin
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7.6 Sliding Mode Control 153 u = B
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7.6 Sliding Mode Control 155 Practi
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7.7 Adaptive Control 157 of gravity
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Let us consider the scalar function
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7.7 Adaptive Control 161 The vehicl
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[deg] 3 2.5 2 1.5 1 0.5 7.8 Output
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7.8 Output Feedback Control 165 It
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7.8 Output Feedback Control 167 whe
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7.8 Output Feedback Control 169 C T
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7.8 Output Feedback Control 171 wit
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[m] [deg] [deg] 0.1 0.05 0 −0.05
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[m] [-] [deg] x 10−3 10 8 6 4 2 0
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[Nm] [Nm] [Nm] 500 0 −500 50 0
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[m] [-] [deg] x 10−3 10 8 6 4 2 0
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[N] [N] [N] 20 0 −20 40 20 0 −2
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[Nm] [Nm] [Nm] 50 0 −50 350 300 2
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7.9 Virtual Decomposition Based Con
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joint torques [Nm] 200 0 −200 −
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e.e. orientation error [deg] 2 1 0
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vehicle position [m] 0.1 0.05 0 −
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8. Interaction Control of UVMSs 8.1
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8.3 Impedance Control 203 8.2 Dexte
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8.4 External Force Control 205 The
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8.4 External Force Control 207 be f
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Page 245 and 246: 226 9. Coordinated Control of Plato
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Page 259 and 260: 240 A. Mathematical models ⎡ 6 .
Page 261 and 262: 242 A. Mathematical models using th
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Page 265 and 266: References 1. Alekseev Y.K., Kosten
Page 267 and 268: References 249 28. Antonelli G.and
Page 269 and 270: References 251 62. Caccia M., Indiv
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Page 273 and 274: References 255 134. Garcia R., Puig
Page 275 and 276: References 257 168. Kato N. and Lan
Page 277 and 278: References 259 mera. In: IEEE Inter
Page 279: References 261 235. Podder T.K. and
Page 283: References 265 310. Yoerger D.R., S
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