PhD thesis (Giovanni Indiveri)

Tue May 25 06:58:37 EDT 1999

Dear Collegues,

my PhD thesis "Modelling and Identification of Underwater 
Robotic" is available in pdf format at the URL:

http://www.gmd.gr.jp/JRL/publications.html#98

Please find in the following its abstract and table of contents.

Best wishes,

                      Giovanni Indiveri   

ABSTRACT  

Whatever is the strategy pursued to design a control system or 
a state estimation filter for an underwater robotic system the 
knowledge of its identified model is very important. As far as 
ROVs are concerned the results presented in  this thesis 
suggest that low cost on board sensor based identification is 
feasible: the detailed analysis of the residual least square
costs and of the parameter estimated variances show that a 
decoupled vehicle model can be successfully identified by 
swimming pool test provided that a suitable identification 
procedure is designed and implemented. A two step 
identification procedure has been designed on the basis of: 
(i) the vehicle model structure, which has been deeply 
analyzed in the first part of this work, (ii) the type of 
available sensors and (iii) the actuator dynamics. First the 
drag coefficients are evaluated by constant speed tests and
afterwards with the aid of their knowledge a sub-optimal 
sinusoidal input thrust is  designed in order to identify the 
inertia parameters. Extensive experimental activity on the 
ROMEO ROV of CNR-IAN has shown the effectiveness of such  
approach. Moreover it has been shown that the standard unmanned 
underwater vehicle models may need, as for the ROMEO  ROV, to 
take into account propeller-propeller and propeller-hull 
interactions that have a most relevant influence on the system 
dynamics (up to 50% of efficiency loss in the applied thrust 
with respect to the nominal model). It has been shown that such 
phenomena can be correctly modelled by an efficiency parameter 
and experimental results concerning its identification on a 
real system have  been extensively analyzed. The parameter 
estimated variances are generally
relatively low, specially for the drag coefficients, confirming 
the effectiveness of the adopted identification scheme. The 
surge drag coefficients have been estimated relatively to two 
different vehicle payload configurations, i.e. carrying a 
plankton sampling device or a Doppler
velocimeter (see chapter 4 for details), and the results show 
that in the considered surge velocity range (|u| < 1 m/s) the 
drag coefficients are different, but perhaps less then 
expected. Moreover it has been shown that in the usual 
operating yaw rate range (< 10 deg /s) drag is better modeled 
by a simple linear term rather then both a linear and a 
quadratic one. This is interesting as it suggests that the 
control system of the yaw axis of slow motion open frame ROV 
can be realized by standard linear control techniques.
For a detailed description of the identification procedure and 
of the identification results of the ROMEO ROV consult chapter 
4. In the last part of this thesis the issue of planar motion 
control of a nonholonomic vehicle has been addressed. Inspired 
by the previous works of Casalino et al. and Aicardi et al. 
regarding a unicycle like kinematic model, a novel globally
asymptotically convergent smooth feedback control law for the 
point stabilization of a car-like robot has been developed. The 
resulting linear velocity does not change sign, curvature is 
bounded and the target is asymptotically approached on a 
straight line. Applications to the control of underwater  
vehicles are discussed and extensive simulations are performed 
in order to analyze the algorithms behaviour with respect to 
actuator saturation. It is analytically shown that convergence 
is achieved also in presence of actuator saturation and 
simulations are performed to evaluate the control law
performance with and without actuator saturation. Moreover the 
generation of smooth paths having minimum square curvature, 
integrated over length, is  addressed and solved with 
variational calculus in 3D for an arbitrary curve 
parametrization. The plane projection of such paths are shown 
to be least yaw drag energy paths for the 2D underwater motion 
of rigid bodies. 

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TABLE OF CONTENTS

1  Introduction      9
    1.1  Motivations and Objectives  9
    1.2  Outline of the work  11
    1.3  Acknowledgments  12

2  Kinematics  13
    2.1  Vectors  13
    2.1.1  Vector notation  13
    2.1.2  Time derivatives of vectors  14
        Poisson Formula  15
        Velocity composition rules  17
    2.1.3  On useful vector operations properties  19

3  Dynamics  21
    3.1  Rigid body Newton-Euler equations  21

    3.2  Fluid forces and moments on a rigid body  26
    3.2.1  The Navier Stokes equation  26
    3.2.2  Viscous effects  28
        Viscous drag forces  28
        Lift forces  29
        Added mass effects  30
        On the properties of ideal fluids  30
        Dynamic pressure forces and moments on a rigid body  33
    3.2.4  Current effects  36
    3.2.5  Weight and buoyancy  37

    3.3  Underwater Remotely Operated Vehicles Model  37
    3.3.1  Thruster dynamics  38
    3.3.2  Overall ROV Model  40
    3.4  Underwater Manipulator Model  41

4  Identification  43
    4.1  Estimation approach  43
    4.1.1  Least Squares Technique  44
    4.1.2  Consistency and Efficiency  47
    4.1.3  On the normal distribution case  47
    4.1.4  Measurement variance estimation  49

    4.2  On board sensor based ROV identification  49
    4.2.1  Model structure  50
    4.2.2  Thruster model identification  54
    4.2.3  Off line velocity estimation  55
    4.2.4  Heave model identification  58
    4.2.5  Yaw model identification  70
    4.2.6  Surge model identification  84
    4.2.7  Sway model identification  89
    4.2.8  Inertia parameters identification  94
    4.2.9  Surge inertia parameter identification  97
    4.2.10  Yaw inertia parameter identification  100

    4.3  Summary  105

5  Motion control and path planning  107
    5.1  2D motion control of a nonholonomic vehicle  107
    5.1.1  A state feedback solution for the unicycle model  109
    5.1.2  A state feedback solution for a more general model  112

    5.2  Path Planning  126
    5.2.1  Curvature  128
    5.2.2  Planning criterion: a variational calculus approach  129
    5.2.3 Solution properties 135
    5.2.4 Solution examples 137

References  145

___________________________________________________________
Giovanni Indiveri, Dr. Visiting Researcher at
GMD-Japan Research Laboratory, Kitakyushu, Japan.
mailto:giovanni.indiveri at gmd.de _URL__http://www.gmd.gr.jp,
voice +81 93 512 1566 /// fax + 81 93 512 1588
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