1 challenge the future ship motion compensation platform for high payloads dynamic analysis and...
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![Page 1: 1 Challenge the future Ship motion compensation platform for high payloads dynamic analysis and control MSc Project at GustoMSC – Wouter de Zeeuw Prof.dr](https://reader036.vdocuments.us/reader036/viewer/2022062305/5697bfc81a28abf838ca83a7/html5/thumbnails/1.jpg)
1Challenge the future
Ship motion compensation platform for high payloads dynamic analysis and control
MSc Project at GustoMSC – Wouter de ZeeuwProf.dr. D.J. Rixen, Ir. M. Wondergem
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2Challenge the future
Introduction: Pooltable on cruise ship
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3Challenge the future
Two ship motion compensation platforms:Ampelmann (personnel) Bargemaster (~400 tonnes)
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Feed the components to the site Jack up and install
Offshore windturbine installation with Jack-up units Present method
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Goal: Complete windturbine installation from a floating unit
1000[t]
400[t](concept of competitor)
Motion stabilizing platform to extend operating limits
Fast feeder barges
Jack up unit stays at site
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Small overview
Preliminary 2D model1. Analysis of Ampelmann scalemodel tests2. 3D modeling of new mechanism on ship3. Controlling the system
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7Challenge the future
Goal: Complete windturbine installation from a floating unit
Preliminary 2D model showed feasibility ...
400[t](concept of competitor)
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8Challenge the future
Goal: Complete windturbine installation from a floating unit
Preliminary 2D model showed feasibility but dynamic instability
400[t](concept of competitor)
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9Challenge the future
1. (In-)stability due to the quasistatic control?Similar mass system: Ampelmann scale model tests
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10Challenge the future
Maximum real part of eigenvalues of system matrix. 1 parameter varied around maximum likelihood estim.
1. Stability of the fitted linear model
All parameters as in fit of first 15 seconds
e.g. cH times 2 (double the hydrodyn. damping) others identical
UNSTABLE
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1. Stability of the fitted linear modelMaximum real part of eigenvalues of system matrix.
1 parameter varied around maximum likelihood estim.
• Adding hydro-damping stabilizes
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12Challenge the future
1. Stability of the fitted linear modelMaximum real part of eigenvalues of system matrix.
1 parameter varied around maximum likelihood estim.
• The damping on opposite movements is a destabilizing factor, possible unmodeled nonlinearities
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1. Stability of the fitted linear modelMaximum real part of eigenvalues of system matrix.
1 parameter varied around maximum likelihood estim.
• The proportional control has stable and unstable settings
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2. 3D modeling - ship movements
• Accelerations due to planar movements surge, sway and yaw are smaller than due to off planar movements
• Platform should compensate heave, roll and pitch
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2. 3D modeling - platform mechanism
• New mechanism for a 3 degree of freedom platform• Planar movements are constrained by 3 Sarrus type
linkages• Force vs. Reach variable via α
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2. 3D modeling - hydrodynamicsBarge panel model(35x115m)
State-Space approx. of wave radiation terms
External wave field realization
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2. 3D modeling - vessel+platform
• Lagrangian dynamics (body fixed) • Extension of serial robot on ship to parallel robots
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2. 3D modeling - total dynamics
• Nonlinear kinematics• Coriolis terms • Pose dep. mass matrix
• External waveloads• Hydrostatics• Hydrodynamics
• Wave radiation• Added mass/damping
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19Challenge the future
2. 3D modeling - total dynamics
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3. Controllers - Naïve Quasistatic vs. Model Based
Quasistatic:• Calculate leg length error assuming fixed boat
position• 2 Proportional-Integral-Derivative (PID) controllers
• On mean error• On asymmetric errors
Model Based:• Nonlinear Model Predictive Control
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3. Control - Nonlinear Model Predictive Control
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22Challenge the future
3. Control - Nonlinear Model Predictive Control
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Visualizations
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24Challenge the future
Visualizations
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25Challenge the future
Heave-Roll-Pitch in storm conditionsHead sea, seastate Hs=4m T1=6.5s.
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Energy usage in disturbance rejectionMilder sea
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Conclusions
• The scalemodel roll instability can be reproduced by a linear model with quasistatic control and influential parameters can be recognized.
• The coupled ship - parallel platform dynamics are derived and he new platform can compensate the ship movements.
• MPC is shown to be a successful candidate for control, requires less power than PID in disturbance rejection and is less hard to tune and to stabilize.
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28Challenge the future
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29Challenge the future
Thank you. Questions?
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30Challenge the future
#1: Second degree model fit, technique
Fitting technique:
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#1b: Second degree model fit, results
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#2: Kinematics – leg joint velocity Jacobian construction
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#3: Hydrodynamics – rad forces
Retardation forces (vector):
Cummins eqn. in hydrodyn. ref. frame:
State space approx. per radiation component (scalar):
Known values via hydrodynamic code (WAMIT):
Approx. model: (Gauss-Newton iter)
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#4a: Dynamics – Pose dep. mass matrix
(Relative velocity)
(ref. frame transf.)
(notation)
(expand)
The total mass matrix is now (platform) pose dependent
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35Challenge the future
#4b: Dynamics - Lagrange
(euler angle rates)(body fixed general velocities)