Underwater Robots - Gianluca Antonelli.pdf

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140 6. Kinematic Control of UVMSs The use of techniques well known in robotics such asthe task priority approach seems to offer good results. They allow toreliably exploit the redundancy and do not require compensation ofthe system’s dynamics. Asit will be shown in Chap. 8, kinematic control techniques can be successfully integrated with interaction control schemes.
7. Dynamic Control of UVMSs 7.1 Introduction In Chap. 2the equations ofmotion of Underwater Vehicle-Manipulator Systems (UVMSs) have been presented. Their expression in matrix form (2.71), is formally close to the equations of motion ofground fixed manipulators for which awide control literature exists. This has suggested asuitable translation/implementation of existing control algorithms. However, some differences, crucial from the control aspect, need to be underlined. UVMSs are complex systems characterized by several strong constraints: • Uncertainty in the model knowledge, mainly due tothe poor knowledge of the hydrodynamic effects; • Complexity ofthe mathematical model; • Kinematic redundancy of the system; • Difficulty tocontrol the vehicle in hovering, mainly due to the poor thrusters performance; • Dynamic coupling between vehicle and manipulator; • Low bandwidth of the sensor’s readings. In [197, 198] adiscrete adaptivecontrol strategyfor coordinated control of UVMSs is presented. Numerical simulations, on aplanar task, show that the use of acentralized controller, better than two separate controllers, one for the vehicle and one for the manipulator, guarantees performance improvement. Reference [124] shows an adaptive macro-micro control for UVMSs. Inverse kinematics is obtained by inversion of the Jacobian matrix; hence, a manipulator with 6degrees of freedom is required. Astability analysis in Lyapunov sense is provided. An adaptivecontrol lawfor an underwatermanipulatorisproposed in [59]. Aself-tuning PID controller is developed and tested in simulation on a2link manipulator with fixed base. In [190] too, an underwater manipulator with fixed base is considered. Adescription of atelerobotic control system is provided in [181]. The use of multiple manipulators to be used asstabilizing paddles is investigated by means of simulations in [168]. Those concern avehicle carrying a6-DOF manipulator plus apair of 2-link manipulators counteracting the interaction force between vehicle and manipulator aspaddles. G. Antonelli: Underwater Robots, 2nd Edition, STAR 2, pp. 141–200, 2006. © Springer-Verlag Berlin Heidelberg 2006
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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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Page 127 and 128: 6.2 Kinematic Control 107 UVMS. Thi
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7.9 Virtual Decomposition Based Con
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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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8.4 External Force Control 209 that
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8.4 External Force Control 211 UVMS
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[N] [m] 350 300 250 200 150 100 50
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[deg] [deg] 10 5 0 −5 −10 50 40
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8.5 Explicit Force Control 217 wher
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8.5 Explicit Force Control 219 wher
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[m] [deg] 0.2 0.1 0 −0.1 8.5 Expl
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[m] [deg] 0.2 0.1 0 −0.1 −0.2 0
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226 9. Coordinated Control of Plato
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238 10. Concluding Remarks control
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240 A. Mathematical models ⎡ 6 .
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242 A. Mathematical models using th
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244 A. Mathematical models L = 2 m
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References 1. Alekseev Y.K., Kosten
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References 249 28. Antonelli G.and
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References 251 62. Caccia M., Indiv
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References 253 96. Cui Y. and Sarka
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References 255 134. Garcia R., Puig
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References 257 168. Kato N. and Lan
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References 259 mera. In: IEEE Inter
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References 261 235. Podder T.K. and
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References 263 273. Solvang B., Den
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References 265 310. Yoerger D.R., S
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