Underwater Robots - Gianluca Antonelli.pdf

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198 7. Dynamic Control of UVMSs vehicle moments [Nm] 500 0 −500 0 10 20 30 time [s] Fig. 7.34. Virtual decomposition control +proper adaptive action. Vehicle control moments joint torques [Nm] 200 0 −200 −400 −600 0 10 20 30 time [s] Fig. 7.35. Virtual decomposition control +proper adaptive action. Joint control torques be motivated by the effect of the current, its value is decreasing to the null value according to the control gains. 7.10 Conclusions In this Chapter an overview of possible control strategies for UVMSs has been presented. In view of these first, preliminary, results, it can be observed that the simple translation of control strategies developed for industrial robotics is not possible. The reason can be found both in the different technical characteristics of actuating/sensing system and inthe different nature of the K N τ q 2 M τ q 1 τ q 3
vehicle position [m] 0.1 0.05 0 −0.05 z x −0.1 0 10 20 30 time [s] y 7.10 Conclusions 199 Fig. 7.36. Virtual decomposition control +proper adaptiveaction. Vehicleposition vehicle orientation [deg] 4 2 0 −2 φ −4 0 10 20 30 time [s] Fig. 7.37. Virtual decomposition control +proper adaptive action. Vehicle orientation forces that act on asubmerged body. Asshown in Chapter 3,neglecting the physical nature ofthese forces can cause the controller to feed the system with adisturbance rather than aproper control action. At the same time, an UVMS is acomplex system, neglecting the computational aspect can lead the designer todevelop acontroller for which the tuning and wet-test phase might beunpractical. Starting from the simulation phase it might beappropriate to test simplified version of the controllers. Among the control strategies analyzed the Virtual Decomposition approach, merged with the proper adaptation action, has several appealing characteristic: it is adaptive in the dynamic parameters; it is based on a Newton-Euler formulation that keep limited the computational burden; it is ψ θ
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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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Page 177 and 178: 7.7 Adaptive Control 157 of gravity
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Page 181 and 182: 7.7 Adaptive Control 161 The vehicl
Page 183 and 184: [deg] 3 2.5 2 1.5 1 0.5 7.8 Output
Page 185 and 186: 7.8 Output Feedback Control 165 It
Page 187 and 188: 7.8 Output Feedback Control 167 whe
Page 189 and 190: 7.8 Output Feedback Control 169 C T
Page 191 and 192: 7.8 Output Feedback Control 171 wit
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Page 195 and 196: [m] [-] [deg] x 10−3 10 8 6 4 2 0
Page 197 and 198: [Nm] [Nm] [Nm] 500 0 −500 50 0
Page 199 and 200: [m] [-] [deg] x 10−3 10 8 6 4 2 0
Page 201 and 202: [N] [N] [N] 20 0 −20 40 20 0 −2
Page 203 and 204: [Nm] [Nm] [Nm] 50 0 −50 350 300 2
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Page 217: e.e. orientation error [deg] 2 1 0
Page 221 and 222: 8. Interaction Control of UVMSs 8.1
Page 223 and 224: 8.3 Impedance Control 203 8.2 Dexte
Page 225 and 226: 8.4 External Force Control 205 The
Page 227 and 228: 8.4 External Force Control 207 be f
Page 229 and 230: 8.4 External Force Control 209 that
Page 231 and 232: 8.4 External Force Control 211 UVMS
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Page 237 and 238: 8.5 Explicit Force Control 217 wher
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Page 241 and 242: [m] [deg] 0.2 0.1 0 −0.1 8.5 Expl
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Page 245 and 246: 226 9. Coordinated Control of Plato
Page 257 and 258: 238 10. Concluding Remarks control
Page 259 and 260: 240 A. Mathematical models ⎡ 6 .
Page 261 and 262: 242 A. Mathematical models using th
Page 263 and 264: 244 A. Mathematical models L = 2 m
Page 265 and 266: References 1. Alekseev Y.K., Kosten
Page 267 and 268: 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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