Underwater Robots - Gianluca Antonelli.pdf

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4.5 Experiments 89 Fig. 4.7. Expected and measured motor currents for the vehicle Romeo in case of flooded thruster (courtesy of M. Caccia, National Research Council-ISSIA) and does not make use of thruster model neither it needs the vehicle acceleration as required bythe theory; the block diagram, thus, is simply given by Figure 4.8. Details on the control law are given in the referenced papers, the basic formulation ofthe controller is given by: u v = E † [(¨η d − β )+K v ˙˜η + K p ˜η ] (4.1) where K v and K v are control gains, the vector ˜η is the position/orientation error, β represents the compensation of the nonlinear terms of the equation of motions. The matrix E takes into account the TCM matrix, the inertia matrix and the Jacobian matrix that converts body-fixed toinertial-fixed velocities. Generalization about control ofadesired task is given in [233]. The experiments validated the proposed approach; inFigure 4.9 the voltages are shown: it can be recognized that thrusters 2and 6(one horizontal and one vertical) are turned off at t =260 sand t =300 s, respectively, this causes anaugmentation of the chattering of the remaining thrusters that, however, still can perform the desired task (Figure 4.10).
90 4. Fault Detection/Tolerance Strategies for AUVs and ROVs η d ˙η d ¨η d Vehicle Controller & Fault Tolerant Strategy u d η , ˙η TCM Direct Kinematics τ Vehicle Dynamics Fig. 4.8. Sketch of the fault tolerance strategy implemented by N. Sarkar, T.K. Podder and G. <strong>Antonelli</strong> voltage 1 voltage 2 voltage 3 voltage 4 2 0 −2 2 0 −2 2 0 −2 2 0 −2 Vertical Thrusters 0 100 200 300 400 300 0 100 200 300 400 0 100 200 300 400 0 100 200 time [sec] 300 400 voltage 5 voltage 6 voltage 7 voltage 8 2 0 −2 2 0 −2 2 0 −2 2 0 −2 η ν Horizontal Thrusters 0 100 200 300 400 260 0 100 200 300 400 0 100 200 300 400 0 100 200 time [sec] 300 400 Fig. 4.9. Voltage profile -vertical thrusters (on the left) and horizontal thrusters (on the right) for the N. Sarkar and T.K. Podder algorithm The AUVC described in [42, 212] has been tested on asix-processor version on the Large Diameter Unmanned <strong>Underwater</strong> Vehicle of the Naval Undersea Warfare Center.
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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
Page 59 and 60: y z 2.8 Kinematics of Manipulators
Page 61 and 62: 2.9 Dynamics ofUnderwater Vehicle-M
Page 63 and 64: 2.9 Dynamics ofUnderwater Vehicle-M
Page 65 and 66: 2.11 Identification 43 f e = K ( x
Page 67 and 68: 3. Dynamic Control of 6-DOF AUVs 3.
Page 69 and 70: 3.2 Earth-Fixed-Frame-Based, Model-
Page 71 and 72: o x z o b z b x b 3.3 Earth-Fixed-F
Page 73 and 74: 3.4 Vehicle-Fixed-Frame-Based, Mode
Page 75 and 76: o o b y x y b x b 3.5 Model-Based C
Page 77 and 78: 3.6 Mixed Earth/Vehicle-Fixed-Frame
Page 79 and 80: 3.7 Jacobian-Transpose-Based Contro
Page 81 and 82: 3.8 Comparison Among Controllers 59
Page 83 and 84: 3.9 Numerical Comparison Among the
Page 87 and 88: force [N] moment [Nm] 20 10 0 −10
Page 101 and 102: 80 4. Fault Detection/Tolerance Str
Page 109: 88 4. Fault Detection/Tolerance Str
Page 113 and 114: 5. Experiments of Dynamic Control o
Page 115 and 116: 5.3 Experiments of Dynamic Control
Page 117 and 118: [m] [m] 5 4 3 2 1 0 0 100 200 300 4
Page 119 and 120: 5.3 Experiments of Dynamic Control
Page 121 and 122: 5.4 Experiments of Fault Tolerance
Page 123 and 124: [deg] 120 100 80 60 40 20 0 −20 5
Page 125 and 126: 6. Kinematic Control of UVMSs “.
Page 127 and 128: 6.2 Kinematic Control 107 UVMS. Thi
Page 129 and 130: 6.2 Kinematic Control 109 singulari
Page 131 and 132: 6.2 Kinematic Control 111 case of t
Page 133 and 134: 6.5 Singularity-Robust Task Priorit
Page 141 and 142: 6.6 Fuzzy Inverse Kinematics 121 It
Page 143 and 144: Simulations 6.6 Fuzzy Inverse Kinem
Page 145 and 146: 6.6 Fuzzy Inverse Kinematics 125 Fi
Page 147 and 148: vehicle attitude [deg] 20 10 0 −1
Page 149 and 150: 6.6 Fuzzy Inverse Kinematics 129 It
Page 151 and 152: [-] 1 0.8 0.6 0.4 0.2 0 close 0 20
Page 155 and 156: joint positions 1-3 [deg] joint pos
Page 159 and 160: 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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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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