Underwater Robots - Gianluca Antonelli.pdf
Underwater Robots - Gianluca Antonelli.pdf
Underwater Robots - Gianluca Antonelli.pdf
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7.8 Output Feedback Control 167<br />
where the matrix L p = blockdiag { l pP I 3 ,lpOI 3 , L pQ} is diagonal positive<br />
definite. The matrix L v =blockdiag { L vP ,lvOI 3 , L vQ} is symmetric and po-<br />
sitive definite, and<br />
A ( � Q e )=blockdiag<br />
�<br />
I 3 , E ( � �<br />
Q e ) / 2 , I n .<br />
The estimated quantities η 1 ,e and q e are computed byintegrating the corresponding<br />
estimated velocities ˙η 1 ,e = R I B ν 1 ,e and ˙q e ,respectively, whereas<br />
theestimated orientation Q e is computed from the estimated angular velocity<br />
ν I 2 ,e = R I B ν 2 ,e via the quaternion propagation rule.<br />
Implementation issues. Implementation ofthe above controller-observer<br />
scheme (7.38),(7.40), requires computation of the dynamic compensation<br />
terms. While this can be done quite effectively for the terms related to rigid<br />
body dynamics, the terms related tohydrodynamic effects are usually affected<br />
by some degree of approximation and/or uncertainty. Besides the use of<br />
adaptive control schemes aimed at on-line estimation ofrelevant model parameters,<br />
e.g. [22, 197, 314], it is important to have an estimate ofthe main<br />
hydrodynamic coefficients.<br />
An estimate of the added mass coefficients can be obtained via strip<br />
theory [127]. Arough approximation of the hydrodynamic damping isobtained<br />
byconsidering only the linear skin friction and the drag generalized<br />
forces.<br />
Another important point concerns the computational complexity associated<br />
with dynamic compensation against the limited computing power typically<br />
available on board. This might suggest the adoption of acontrol law<br />
computationally lighter than the one derived above. Areasonable compromise<br />
between tracking performance and computational burden is achieved<br />
if the compensation of Coriolis, centripetal and damping terms is omitted<br />
resulting in the controller<br />
u = B † � M ( q ) a r + K v ( ζ r − ζ o )+K p e d + g ( q , R I B ) � , (7.41)<br />
with the simplified observer<br />
�<br />
˙z = M ( q ) a r − � L p + L v A ( � �<br />
Q e ) Λ e e e + K p e d<br />
ζ = M − 1 ( q )(z − L v e e ) − Λ e e e ,<br />
(7.42)<br />
The computational load can be further reduced if asuitable constant<br />
diagonal inertia matrix � M is used in lieu of the matrix M ( q ), i.e.,<br />
u = B † � � Mar + K v ( ζ r − ζ o )+K p e d + g ( q , R I B ) � , (7.43)<br />
with the observer<br />
�<br />
˙z = Mar<br />
� − � L p + L v A ( � �<br />
Q e ) Λ e e e + K p e d<br />
�ζ = � − 1<br />
M ( z − L v e e ) − Λ e e e ,<br />
(7.44)