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Journal of Electrical Engineering 4 (2016) 133-149 doi: 10.17265/2328-2223/2016.03.004
Depth and Altitude Control of an AUV Using Buoyancy
Control Device
Mahdi CHOYEKH1, Naomi KATO1, Ryan DEWANTARA1, Hidetaka SENGA1 and Hajime CHIBA2
1. Department of Naval Architecture and Ocean Engineering, Osaka University, Suita, Osaka 565-0871, Japan
2. Department of Merchant Marine, Toyama National College of Technology, Imizu, Toyama 933-0293, Japan
Abstract: A new method for depth control was developed for a spilled oil and blow out gas tracking autonomous buoy robot called SOTAB-I by adjusting its buoyancy control device. It is aimed to work for any target depth. The new method relies on buoyancy variation model with a depth that was established based on experimental data. The depth controller was verified at sea experiments in the Toyama Bay in Japan and showed good performance. The method could further be adapted to altitude control by combining the altitude data measured from bottom tracking through a progressive depth control. The method was verified at the sea experiments in Toyama in March 2016 and showed that the algorithm succeeded to bring the robot to the target altitude.
Key words: AUV, depth control, buoyancy device.
1. Introduction
Oil spills produced by accidents from oil tankers and
blowouts of oil and gas from offshore platforms cause
tremendous damage to the environment as well as to
marine and human life [1]. To prevent oil and gas that
are accidentally released from deep water from
spreading and causing further damage to the
environment over time, early detection and monitoring
systems can be deployed to the area where underwater
releases of the oil and gas first occurred. Monitoring
systems can provide a rapid inspection of the area by
detecting chemical substances and collecting
oceanographic data necessary for enhancing the
accuracy of simulation of behavior of oil and gas.
Due to their compactness, the use of AUVs for
full-water surveying is being adopted increasingly [2,
3]. Among the existing types of underwater robots used
to autonomously monitor marine environments in 3-D
space from sea surface to seabed over the long term is
the Argo Float [4] that floats vertically and repeats
descending and ascending in the vertical direction by
using a buoyancy control device. However, it does not
Corresponding author: Mahdi CHOYEKH, Ph.D. student, research fields: naval architecture and ocean engineering.
have a function of active movement in the horizontal
direction. Another method is the underwater glider [5],
which has a streamlined body with fixed wings. It can
descend and ascend also by using a buoyancy control
device, while it moves in the horizontal plane like a
glider for long distance. However, the ratio of vertical
movement distance to horizontal movement distance is
small. An AUV (autonomous underwater vehicle)
called SOTAB-I (the spilled oil and gas tracking
autonomous buoy system), that provides functionality
that lies midway between profiling buoys and gliders,
is being developed. It was designed not only to move in
the vertical direction by a buoyancy control device, but
also in the horizontal direction by two pairs of
rotational fins. SOTAB-I can perform on-site
measurements of oceanographic data as well as
dissolved chemical substances using underwater mass
spectrometry [6]. SOTAB-I has three main surveying
modes. At the first stage, SOTAB-I performs the water
column survey by adjusting its buoyancy. The rough
mode is used to collect rough data on physical and
chemical characteristics of plumes by repeating
descending and ascending on an imaginary circular
cylinder centered at the blowout position of oil and gas
D DAVID PUBLISHING
Depth and Altitude Control of an AUV Using Buoyancy Control Device
134
through the variation of buoyancy and movable wings’
angles. Finally, in case the UMS detects a high
concentration of any particular substance, a precise
guidance mode will be conducted to track and survey
its detailed characteristics by repeating descending and
ascending within the plume. The photograph mode
enables us to have a large visual overview of the area
around the blowout position of oil and gas by taking
pictures of the seabed and making image mosaicking.
SOTAB-I moves laterally using horizontal thrusters
along diagonal lines of a polygon with a radius of 5 m
centered on the blowout position of oil and gas.
Therefore, the depth control is a very important task in
the surveying effort which requires particular attention.
There are several methods used to control the depth
of AUVs. With normal horizontal type AUVs, the
depth control is performed by horizontal wings. For the
vertical type AUVs, a buoyancy control device is
normally used for depth control. There exist a variety
of mechanisms to adjust the buoyancy. In the
submarines for example, the amount of the air/seawater
of trim or ballast tanks is controlled to adjust the
buoyancy. When the submarine is on the surface, air is
filled in the ballast and the submarine becomes
positively buoyant. To start diving, water is introduced
into the ballast tanks while the air is vented outside
until it becomes negatively buoyant leading the
submarine to sink. Compressed air is stored in flasks to
adjust the amount of water inside the ballast tank
during operation. Another widely employed
mechanism in AUVs is to adjust the volume of the
robot through a device that compresses and expands the
air contained in a cylinder. This mechanism is
characterized by its reliability and its relative fast
response. However, the motor pump, used to ensure the
compression and the expansion of the air, generates
noise. Additionally, when the robot is decreasing its
buoyancy, an amount of the ballast water (seawater) is
pulled from one region and then, may be dumped in
another region to increase buoyancy. This represents a
risk of dumping living organisms in an environment
different from their original inhabiting region, which
may harm their new environment. This problem is
referred as the ballast water problem [7, 8]. Among
other existing technologies, there is the metal bellow
mechanism, which imitates the change of state of the
spermaceti oil from liquid to solid and vice versa,
leading to change of density, in the sperm whale [9].
Similarly, AUV using metal bellow mechanism relies
on the change of state of a low melting point liquid,
such as wax [10] or oil [11], by adjusting its
temperature. This mechanism does not make noise and
presents an ecological advantage over other systems
since it does not involve any discharging of ballast
materials, eliminating the ballast water problem.
However, results show that their response time is slow
and is energetically costly since the temperature of the
oil should be maintained. A third mechanism imitates
ray-finned fish, which adjust the volume of their
bladders to adjust their buoyancy [12]. They employ
polymer buoyancy control device [13]. Electrolysis is
used to generate pure hydrogen, which is a clean gas, in
order to expand the volume of an artificial bladder
leading to a displacement of water and an increase of
buoyancy. To reduce the robot buoyancy, extra amount
of gases are simply released outside via a valve. These
systems are characterized by their silent operation.
However, they are more oriented for small devices
operating near the sea surface where the water pressure
is not significant. Due to the reliability and the fast
response as well as their low power consumption, the
buoyancy variation through the adjustment of the air
volume in a cylinder mechanism was employed. The
ballast water problem does not apply for SOTAB-I
since it is designed to operate around the same region
of the blow out gas. The noise caused by the motor
pump may be reduced by choosing a high quality
actuator.
For the same control mechanism, there exist several
control strategies. An implementation of a cascaded
velocity-position PID controller was used in a coastal
profiling float by Ref. [14]. The method consists of
Depth and Altitude Control of an AUV Using Buoyancy Control Device
135
adjusting the velocity set point according to depth error
between the current and target depths. The vertical
velocity is controlled through a PID controller to
achieve the desired depth. The algorithm succeeded to
achieve the desired depth near the sea surface, but at a
high energy cost. Another control strategy is employed
in the underwater gliders where the buoyancy control
device is performed simultaneously with a mechanism
of gravity center movement in horizontal plane. On the
other hand, Argo float uses only buoyancy device to
adjust their depth. To do so, the float relies on the
establishment of a highly accurate ballasting curve [15].
This requires a high precision ballasting experiment to
adjust the robot’s density in a way to become equal to
the density of the seawater, which will be measured by
a highly accurate CTD sensor, at the designated
parking depth. This will lead the robot to reach its
neutral buoyancy point.
There are many challenges and constraints
associated with depth control of underwater vehicle.
For instance, at-sea experiments require enormous
financial and logistic resources limiting the
experiments time. Hence, it is important that the
program should be easy to implement and repeatedly
verified by simulating programs before its real
deployment. On the other hand, environmental
constraints like a considerable variation of the density
of water between the sea surface and the seabed bring
complications in the control because they lead to the
variation of the neutral buoyancy value of the robot.
Even if the neutral buoyancy of the robot is determined
accurately at a certain spatial condition, there is no
guarantee that the robot will keep its vertical position
due to the up-welling and down-welling water currents.
Other constraints are represented by the hardware
limitations. In fact, the buoyancy device employed has
three controlling states: it can be controlled to increase
the buoyancy, decrease it or stay idle. However, it is
not possible to change the rate of variation directly. In
addition, the rate of change of buoyancy is relatively
slow, not symmetric in both directions and varies with
depth. Moreover, the change of the buoyancy variation
orientation is not instantaneous, there is a lag time of 2
s between each change of state. The oil level sensor has
also an inaccuracy within ±0.1%. Previously, a PID
controller was developed for depth control [16]. It gave
good performances and small overshoot, but only for a
depth range up to 100 m. Beyond that limit, significant
overshoot was reported. The previous controller relied
on a very accurate determination of the neutral
buoyancy. In addition, the PID control parameters were
not adaptive. Besides, it does not enable to freeze the
robot at the target depth. For the lacks mentioned
before, it is necessary to develop a new controller that
overcomes the shortening and take in consideration the
environmental and hardware constraints. A new
method for depth control was developed. It is aimed to
work for any target depth and to freeze the robot at the
target depth. The method relies mainly on the
buoyancy variation model with depth established based
on tank and at-sea experimental data. The paper is
organized as follows: Section 2 gives an overview of
SOTAB-I hardware and its buoyancy device. Section 3
studies the buoyancy variation at tank and sea
experiments and establishes its model. Section 4 and 5
deal, respectively, with the depth control and the
altitude control algorithms and the experimental results
obtained of their execution in Toyama Bay
experiments in March 2016. The final section gives the
conclusions of the work.
2. SOTAB-I Overview and Hardware Description
2.1 Outlines of SOTAB-I
The SOTAB-I is 2.5 m long and weighs 325 kg. It
can be submerged in water as deep as 2,000 m. It is able
to descend and ascend by adjusting its buoyancy using
a buoyancy control device while changing its
orientation through two pairs of movable wings. The
SOTAB-I can also move in horizontal and vertical
directions using two pairs of horizontal and vertical
thrusters. A visual overview of SOTAB-I is illustrated
136
in Fig. 1, and
Table 1. Th
installed on
When the
(wireless loc
communicat
transmission
the mothers
through the
The robot
GPS (global
determine th
where the ro
the USBL (
position of t
depth data f
within the bo
DVL (Dopp
robot’s veloc
Fig. 2 Arran
Dep
d its main cha
he arrangem
SOTAB-I is
e robot floats
cal area netw
tion transceiv
n. When the ro
ship and the
acoustic mod
t tracking on t
l positioning s
he robot’s ab
obot is subm
(ultra-short b
the robot in t
from the CT
ottom trackin
pler velocity
cities. The ro
ngement of dev
pth and Altitu
aracteristics a
ment of devi
shown in Fig
on the sea s
work) and an
ver module a
obot is underw
SOTAB-I c
dem.
the sea surfac
system) recei
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merged, tracki
baseline) syst
the water col
D sensor. W
ng altitude fro
logger) is
bot motion an
vices and senso
ude Control o
are summarize
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g. 2.
urface, a WL
n iridium sate
are used for
water, the use
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iver that serve
tion. In the
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When the robo
om the seabed
able to mea
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ors installed on
of an AUV Us
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icate
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n SOTAB-I.
ing Buoyancy
en by the
asurement un
. 1 SOTAB-I
ble 1 Principa
tal length [mm]
ameter [mm]
eight in air [kg]
eight in water [k
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compass a
nit).
robot.
al particulars o
] 2,
66
3
kg] ±
vice
and the IM
of SOTAB-I.
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67
11.7
3.8
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and orientat
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and physical
obtain a vis
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bladder and
serves to au
brake is use
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external pr
In total, six
buoyancy de
power suppl
and another
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Fig. 4 dep
in the reser
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Dep
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with a UMS to
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the internal
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injection of
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digital input
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log output tha
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ed to measur
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o determine th
f the dissolve
tation of blow
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trol device,
ts oil between
oil reservoir
ing and closi
pump (Fig.
oil into the
MPa is 243 mL
om the blad
dition, it is
s are employ
tal input serv
input is used
To control
d to run/disab
n direction. On
rake. The feed
hat report th
at provides th
tionship betw
he volume o
re in the re
ude Control o
re the magni
ers. SOTAB
he characteri
ed gas and oil
wouts of plu
equipped wit
an oil hydra
n the externa
r. A motor v
ing cycles, an
3). The flow
e bladder at
L/min, and du
dder at the s
s 349 mL/m
yed to control
ves to control
to open the v
the motor pu
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he oil level.
ween the pres
f the oil in
eservoir” is
of an AUV Us
tude
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umes
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the
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1.62
and
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ssure applied
ervoir cylind
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oil volume
iation of rob
hen the oil roo
When the oil
208 V. Becau
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volume of th
linear volu
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ume change w
ically equal to
. 4 Relationshhe oil reservoir
y Control Dev
d by the hy
der. The ma
pump is 0.03
ear potentiom
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pressure. The
of the reser
bot buoyancy
om is full, the
l room is em
use the reserv
e of the base
otentiometer
he oil in the
ume/output v
an be obtain
with the dens
o 1,024 kg/m
hip between thr.
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ydraulic pum
aximum allo
MPa. The oi
meter whose a
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can be used
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sity of seawa
m3.
he pressure an
137
mp to the oil
owable drain
il reservoir is
analog output
cement under
roportional to
leads to the
in Table 2.
age is 0.3892
put voltage is
ndrical shape
t, the output
to determine
hich explains
ionship. The
ultiplying the
ater, which is
nd the volume
7
l
n
s
t
r
o
e
.
2
s
e
t
e
s
e
e
s
e
138
Table 2 Vamotor.
Mass change (seawater) (g)7,884.8
7,746.6
7,763.2
3,925.7
171.8
0
3. Establis
The objec
model and
needed for t
estimate the
buoyancy fr
buoyancy m
program. It
buoyancy va
period. We
buoyancy v
water depth
at pressure t
3.1 Experim
3.1.1 Pres
Pressure
calculate the
oil in the
direction is
extracts oil f
to the intern
direction.
Based on
change the b
OUT>IN dir
water depth
modeled as
between the
and 20 MPa
direction, th
from 0 up to
Dep
riation of rob
) Volume change (cm3) 7,700.0
7,565.0
7,581.2
3,833.7
167.8
0
shment of t
ctive in this
a buoyancy
the depth con
e time needed
rom its curren
model is also
enables to e
alue from its
consider es
ariation from
based on the
ank and at-se
ments Results o
ssure Tank Ex
tank exper
e time necess
reservoir in
when the oi
from the exte
nal oil reserv
n Fig. 5 and
buoyancy cor
rection is con
h). From 10
a linear fu
full scale va
a is less than
he buoyancy v
o 10 MPa. B
pth and Altitu
bot buoyancy
Potentiometeoutput voltag1.621
1.599
1.602
1.012
0.443
0.389
the Buoyan
section is to
model. The
ntrol of the ro
d for SOTAB
nt value to a
o needed fo
estimate the
s initial value
stablishing a
m 20 to 85%
e experiments
ea.
of Buoyancy
xperiments
riments were
sary for chan
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ernal oil blad
oir. IN->OUT
Table 3, the
rresponding t
nstant till 10
MPa to 20
unction. The
ariation of buo
n 9 minutes. F
variation tim
Beyond that l
ude Control o
against voltag
er ge (V)
Pressur(MPa)0
0
0.005
0.018
0.030
0.041
ncy Model
establish a t
e time mode
obot. It enable
B-I to chang
target value.
r the simula
variation of
e every samp
a model for
% up to 1,000
s results obta
Variation
e performed
nging 7,500 c
tions. OUT-
pump injects
dder and injec
T is the oppo
e time neede
o 7,500 cc in
MPa (~1,00
Mpa, it can
time differe
oyancy at 0 M
For the IN>O
me is almost s
limit, it beco
of an AUV Us
ge on
re
time
el is
es to
e its
The
ating
f the
pling
the
0 m
ained
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cc of
->IN
and
cts it
osite
ed to
n the
00 m
n be
ence
MPa
OUT
same
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tank
0 to
the
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vari
m a
vari
deg
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vari
line
In
Fig.buo
Tabpres
IN>
OU
ing Buoyancy
ghtly faster.
3.1.2 At-sea E
Fig. 6a confir
k. The buoya
o 100 m. Hen
OUT>IN di
ction. Fig. 6b
March 2015 i
iation in the I
and 700 m w
iation can be
gree polynom
Model of the
Based on th
iation in the O
ear function.
Tc (OU
n the IN>OU
. 5 Relatioyancy variatio
ble 3 Time ssure.
ExternpressurMPa
>OUT
0
10
20
UT>IN
0
10
20
y Control Dev
Experiments
rms the result
ancy variation
nce, the time
irection can
b dates from a
in Toyama Ba
IN>OUT dire
water depths.
e represented
ial function a
e Buoyancy Va
he experimen
OUT>IN dire
UT->IN) = –1
UT direction,
onship betweeon time.
of variation
nal re
Motor rotaspeed rpm
7,865
6,700
5,760
7,865
7,865
8,300
vice
ts obtained in
n rate is almo
e and buoyan
be modeled
an experimen
ay. It shows t
ection from 20
. It shows th
under the fo
as shown in T
Variation with
ntal data, th
ection can be
15.122 * (Bt –
, the main pa
en the press
of robot bu
ation Flow rate
T
cc/min m
331 2
282 2
243 3
331 2
331 2
349 2
n the pressure
st same from
cy models in
d as a linear
nt on the 20th
the buoyancy
0 to 85% at 1
hat buoyancy
form of a 3rd
Table 4.
Depth
he buoyancy
modeled as a
– B) (1)
arameter that
sure and the
uoyancy with
Time
min/7,500 cc
22.6
26.6
30.9
22.6
22.6
21.5
e
m
n
r
h
y
y
d
y
a
)
t
e
h
Fig. 6 Buoyexperiment.
Table 4 Buexperiment.
Direction
OUT>IN
IN>OUT
contributes c
variation spe
and written
function that
Table 5 Com
Experiment 5/25/2015 2:28:43 11/27/2014 9:20:56 11/28/2014 9:48:23
3/20/2015 14:12:33
Dep
(a)
(b) ancy variation
oyancy variat
Depth B
1 to 700 m T
1 m T
700 m T(B
considerably
ed is the depth
under the fo
t depends on
mparison betw
Depth
Air
0~95 m 700 m 0~42 m 0~100 m
95~155 m
155~198 m
198~210 m
pth and Altitu
OUT>IN
IN>OUT
n with depth on
tion model of
Buoyancy variat
Tc = –15.122 * (
Tc = 15.122 * (BTc = 0.0015 * (BBt
2 – B2) + 34.0
in the change
h. The model c
orm of 3rd de
the depth D.
ween the buoya
OrientationOUT>IN IN>OUT OUT>IN IN>OUT OUT>IN IN>OUT
IN>OUT
IN>OUT
IN>OUT
ude Control o
n 20th March
20th March
tion
(Bt – B)
Bt – B) Bt
3 – B3) – 0.26065 * (Bt – B)
e of the buoya
can be general
egree polynom
ancy variation
n Range 95%220%79%220%78%31%
20%
30%4
40%4
of an AUV Us
2015
2015
88 *
ancy
lized
mial
L
coe
buo
esta
foll
Ci (
K
A
A
3.3
and
D
wer
SOT
mod
defi
dev
buo
resu
T
vari
exp
whe
The
exc
sug
dire
the
model and exp
of variation 21% 94% 20% 85% 31% 79%
30%
40%
49%
ing Buoyancy
Tc (IN
C2(D) *
Linear interp
efficients a,
oyancy model
ablished for
lowing equati
(D) for i = {1
Ci (D) = (C
Knowing that
At 700 m C3 =
At 1 m C3 = 0
Comparison
d Experimenta
Data of buoy
re collected
TAB-I and co
del. To estim
fined the rati
viation of the
oyancy variat
ults.
Table 5 sho
iation is cl
periments. Th
en the buoyan
e time estimat
eed 0.5 s per
ggesting a h
ection. On the
maximum va
perimental resu
Tc (experimen1,121 s 1,166 s 859 s 1,274 s 703 s 854 s
178 s
176 s
170 s
y Control Dev
N->OUT) = C
(Bt2 – B2) +
polation and
b and c are
l at a certain d
depths equa
ion shows the
, 2, 3}
Ci (1) – Ci (70
= 0.0015; C2
0; C2 = 0; C1 =
n between Bu
al Data
yancy variatio
from previou
ompared to th
mate the acc
io Time/Ran
e model in s
ion. Table 5
ws the estim
lose to the
he maximum
ncy variation
tion in the OU
1% of buoyan
high accuracy
e other hand, i
alues of devia
ults.
nt) Tc (mod1,119 s 1,164 s 892 s (501,340 s (710s 823 s (50199 s (15184 s (95192 s (15193 s (19169 s (19
vice
3(D) * (Bt3 –
C1(D) * (Bt –
d extrapolat
e used to de
depth based o
al to 1m and
e formula used
00)) * D / (70
= 0.2688; C1
= 15.122.
uoyancy Vari
on time in se
us at-sea exp
he values obt
curacy of the
nge to estim
seconds for e
summarizes
mated time o
values ob
m deviation w
is between 20
UT>IN direct
ncy variation
y of the mo
in the IN->OU
ations were ob
el) Time–0.03–0.03
0 m) +0.56(700 m) +1.01
+0.150 m) –0.6555 m) 5 m)
+2.1 +0.6
55 m) 98 m)
+1.6 +1.5
98 m) –0.11
139
B3) –
– B) (2)
tion of the
etermine the
on the models
d 700m. The
d to calculate
00 – 1) (3)
= 34.065
iation Model
everal ranges
periments of
tained by the
e model, we
ate the time
every 1% of
the obtained
of buoyancy
tained from
was obtained
0% and 30%.
tion does not
n at full range,
odel in that
UT direction,
btained in the
e/range (s/1%)3 3 6 1 5 5
1
9
)
e
e
s
e
e
)
l
s
f
e
e
e
f
d
y
m
d
.
t
,
t
,
e
140
20 to 30%
variation of
model as rel
the model a
model with
depths whic
extrapolation
4. Depth C
4.1 Control A
Dependin
main scenar
robot reache
ascending, l
bring the r
there until
acoustic com
Therefore, w
into two mai
to bring the
target depth
Once the ta
executed to
In the nex
controller an
4.1.1 Pred
As shown
parameters
experiment.
neutral buoy
around it (B
random erro
data (Derr) o
data collecte
Once th
configuratio
executed eve
sensors’ dat
CTD sensor,
measured by
Dep
range, but d
buoyancy. S
liable. It is im
accuracy can
h additional
ch will reduce
n error.
Control
Algorithm
ng on the op
rios to be con
es the target
like in the ro
robot to the
an ascendin
mmunication
we can deco
in steps. As sh
robot from
h (Dt) using a
arget depth is
stabilize it ar
xt part we ex
nd the depth s
dictive Contro
n in Fig. 8, w
of the progr
For instance
yancy (Bn) w
Bm). We also
or of the oil s
of the CTD s
ed in the prev
he program
on is over,
ery second. A
ta, such as th
, and the valu
y a linear po
pth and Altitu
did not excee
o we can con
mportant here
be improved
experiment
e the model
perating mod
nsidered. The
depth and su
ough mode. T
target dept
g order is r
or ascending
ompose the
hown in Fig.
its current de
a predictive
s reached, th
round the targ
xplain in deta
stabilization a
ol
we introduce t
ram at the b
e, the estima
with the marg
o input the v
sensor (Berr)
sensor, based
vious experim
m is exe
the predicti
At first the rob
he depth (D),
ue of the curre
otentiometer
ude Control o
ed 2.1 s per
nsider the ov
e to mention
d by feeding
data at var
interpolation
de, there are
e first is that
ubsequently s
The second i
th and freez
received thro
g timer overf
control prog
7, the first ste
epth (D) to a
depth contro
he second ste
get depth.
ails the predic
algorithm.
the configura
beginning of
ated value of
gin of uncerta
value of sen
and of the d
d on the sens
ments.
ecuted and
ve controlle
bot updates al
provided by
ent buoyancy
image of the
of an AUV Us
1%
erall
that
g the
rious
and
two
t the
tarts
is to
ze it
ough
flow.
gram
ep is
a set
oller.
ep is
ctive
ation
f the
f the
ainty
nsors
depth
sors’
its
er is
ll the
y the
(B),
e oil
leve
such
F
outp
rela
A
of t
Eq.
Fig.
Fig.
Fig.
ing Buoyancy
el. Other data
h as the verti
Fig. 9 show
puts diagram
ated to the pre
At every seco
the time need
(4).
. 7 Depth con
. 8 Predictive
. 9 Predictive
y Control Dev
a can be deriv
cal speed (S)
s the predic
and Table 6
edictive contr
ond, it is poss
ded to reach t
ntrol process.
e depth control
e depth control
vice
ved based on
).
ctive control
defines all th
roller.
ible to have a
the target dep
l flowchart.
l input/output
the raw data,
l inputs and
he parameters
an estimation
pth (Tr) using
diagram.
,
d
s
n
g
Depth and Altitude Control of an AUV Using Buoyancy Control Device
141
Table 6 Definition of the buoyancy control parameters.
Symbol Definition
D Current depth (m). D > 0
Dt Target depth (m)
Dm Margin of tolerance around Dt
S Current speed (m/s). S > 0 Robot descending
Sm Speed margin
B Current buoyancy (%). Range: 20->95%
Bt Output target buoyancy
Bn Neutral buoyancy
Bm Margin of tolerance around the neutral buoyancy Bn
Tc Time needed to change the buoyancy from B to Bt in (s)
Tr Time needed to reach the target depth based on the current speed of the robot
Tm Time margin used for security purpose. It compensates eventual inaccuracy in the buoyancy model
Tr = ((Dt – D) / S) (4)
The buoyancy variation model, established in the
previous section of this paper, enables to estimate the
time (Tc) needed for changing the robot buoyancy from
its current value to the neutral buoyancy. The first step
is based on the continuous estimation of the time to
reach (Tr) and the time to change (Tc) while decreasing
the buoyancy value, till the stop condition is reached.
We introduce Tm, which corresponds to the time error
margin used to compensate eventual inaccuracies in the
buoyancy device model.
If the estimation of Tr > Tc + Tm it means that it is
possible to increase the vertical speed of the robot since
we have enough time to change the buoyancy to its
neutral level. Hence, we decrease the target buoyancy
value.
In the case where Tr <= Tc + Tm, then it means we
have just enough time to change the buoyancy to the
neutral level before the robot reaches its target depth.
Hence, we start to increase the buoyancy of the robot
progressively.
4.1.2 Depth Stabilization
Several algorithms can be used for depth
stabilization. Among the most used are the PID
controllers. However, one of the drawbacks of these
controllers is that they require the actuators to operate
at full time, which increases the power consumption. In
addition, in our robot’s case, the buoyancy variation
speed is not constant and varies with depth.
Furthermore, its variation is not symmetric in both
IN->OUT and OUT->IN directions. For that reason, a
conventional PID controller is not suitable, which
requires the development of an asymmetric PID
controller that adapts its parameters with the robot’s
depth. This will add a lot of complexity to the program
and requires a longer time to implement it and to
validate its performance. For that reason, we chose to
use a heuristic controller for depth stabilization. The
latter provides a simple way to control the depth. It is
based on heuristic rules that enable to adjust the
buoyancy based on the current depth and vertical speed
of the robot. If we take the case where the robot depth
(D) is below the target depth (Dt), we can establish the
following rules, to be executed by priority order:
If the robot is below the maximum tolerated depth
(Dt + Dm), then increase the buoyancy;
If the robot is below Dt and it is descending, then
increase buoyancy;
If the robot is below Dt, but it is ascending fast
above a speed margin (Sm), then decrease buoyancy;
If the robot is below the target depth, and it’s
ascending slowly below (Sm), then the buoyancy
actuator is idle.
Fig. 10 shows the flowchart of all the algorithm. It is
important to mention here that the buoyancy variation
values are limited between Bn + Bm and Bn – Bm.
142
Fig. 10 Heu
Table 7 Par
General param
Target depth
Neutral buoya
Buoyancy ma
Buoyancy con
Buoyancy dev
Predictive con
Time margin
Depth margin
Depth stabiliz
Vertical speed
Depth thresho
Stabilization
4.2 Experim
The dept
Toyama Ba
ordered to re
stay there fo
surface. Hen
3 main step
predictive d
(Step 1). The
heuristic con
for 15 minut
set to its ma
surface (Ste
parameters w
Fig. 11 sh
be observed
depth and fr
Dep
uristic control f
rameter config
meters
(Dt)
ancy (Bn)
argin (Bm)
ntrol threshold
vice accuracy (
ntrol parameter
(Tm)
n (Dm)
zation paramete
d threshold (Sm
old
period
ments Results
th control ex
ay on 17th M
each a set tar
or 15 minute
nce, the contro
ps: In the fi
depth contro
en the depth st
ntrol is execu
tes (Step 2). F
aximum value
ep 3). For th
were configur
hows the resu
d, the robot
freeze there fo
pth and Altitu
flowchart.
uration.
(Bdiff)
(Berr)
rs
ers
m)
xperiment w
March 2016.
rget depth equ
es before asce
ol program ca
irst step, the
l to reach t
tabilization al
uted to freeze
Finally, the ta
e to bring the
at purpose, t
red as shown
ult of the expe
managed to
for 15 minute
ude Control o
Value
500 m
62.5%
2.0%
0.2%
0.05%
Value
20 s
0.5 m
Value
0.02 m/s
5 m
900 s
was conducted
. The robot
ual to 500 m
ending to the
an be divided
e robot uses
the target d
lgorithm using
e the robot d
arget buoyanc
e robot to the
the depth con
n in Table 7.
eriment. As it
reach the ta
es before star
of an AUV Us
d in
was
m and
e sea
into
the
depth
g the
depth
cy is
e sea
ntrol
t can
arget
rting
the
F
spe
Fig.
Fig.
ing Buoyancy
ascent.
Fig. 12a show
ed with dep
. 11 Depth co
. 12 Predictiv
y Control Dev
ws the variati
th under the
ontrol.
(a) Depth V
(b) Depth Vs B
(c) Tc V
ve depth contro
vice
ion of the rob
e effect of th
Vs Speed
Buoyancy
Vs Tr
ol.
bot’s vertical
he buoyancy
l
y
control show
depth (TrDt)
neutral buoy
latter param
be increased
in Fig. 7. It
reach the tar
at a buoyan
algorithm su
speed based
TrDt.
Fig. 13 sh
algorithm.
maintained
tolerance ar
addition, the
robot’s verti
threshold).
In additio
and not 62
program suc
depth.
Fig. 14 s
speed was eq
vertical spee
As a con
succeeded to
overshoot at
a vertical spe
stabilization
the target de
vertical spe
proved its r
buoyancy w
buoyancy, th
depth withou
5. Altitude
There are
SOTAB-I to
photograph
Dep
wn in Fig. 12b
) and the tim
yancy (TcBn)
meters define w
d or decreased
t can be obs
rget depth wi
ncy value ne
ucceeded to
d on the com
hows the res
It shows
the robot s
round the tar
e control pro
ical speed to
n, though the
.5% as set
cceeded in co
shows the ro
qual to 0.4 m/
ed is due to th
nclusion, the
o bring the ro
t a buoyancy
eed close to 0
n algorithm m
epth at a limit
eed. Further
robustness: T
was slightly d
he robot man
ut problem.
e Control
e several op
o get close to t
mode, SOTA
pth and Altitu
b. The time to
me needed t
) are shown
whether the b
d as explained
served that ro
ith a vertical
ear the neut
balance the
mpromise be
sult of the de
that the c
peed within
rget depth eq
ogram succee
o less than 5
e real neutral b
in the progr
ontrolling the
obot’s ascent
/s. The sudde
he change of th
e predictive
bot to the targ
value equal t
0. On the othe
managed to ke
ted overshoot
rmore, the c
Though the e
different from
naged to reach
perating mod
the seabed. F
AB-I needs
ude Control o
o reach the ta
to change to
in Fig. 12c.
buoyancy sho
d in the flowc
obot manage
speed near 0
tral. The con
robot’s ver
etween TcBn
epth stabiliza
control prog
the interva
qual to 5 m
eded to limit
cm/s (check
buoyancy wa
ram, the con
e robot at the
t. The maxim
en variation o
he wings’ ang
control prog
get depth with
to the neutral
er hand, the d
eep the robot
t and a very sm
control prog
estimated neu
m the real neu
h the exact ta
des that req
or example in
to approach
of an AUV Us
arget
o the
The
ould
chart
ed to
m/s
ntrol
rtical
and
ation
gram
al of
m. In
t the
k Sm
as 64%
ntrol
e set
mum
f the
gles.
gram
hout
l and
depth
near
mall
gram
utral
utral
arget
quire
n the
h the
seab
pos
Fig.
Fig.
ing Buoyancy
bed to be abl
ition. Simila
. 13 Depth sta
. 14 Robot’s a
y Control Dev
le to take nea
arly, in the wa
(a) Depth V
(b) Depth Vs B
abilization.
(a) Depth V
(b) Depth Vs B
ascent.
vice
at pictures of
ater column m
Vs Speed
Buoyancy
Vs Speed
Buoyancy
143
the blow out
measurement
3
t
t
144
mode, the ro
to near the se
Hence, it i
controls the
vertical thru
is a risk that
which influ
addition, the
inaccuracies
overcome th
suggest a se
device as an
5.1 Control A
The meth
control algo
altitude cont
robot is onl
seabed when
set target al
range.
Fig. 15 i
control algo
depth contr
control exec
altitude.
Fig. 15 Altit
Dep
obot is require
ea bed to obta
s important
altitude of th
sters to contro
t they mix up
uences the tr
ey will disturb
s in the wat
he previously
econd method
actuator to co
Algorithm
hod consists o
orithm detaile
trol. It is imp
ly able to m
n the bottom
ltitude shoul
illustrates the
orithm. It con
rol followed
cuted to kee
tude control flo
pth and Altitu
ed to dive fro
ain a full wate
to develop
he robot. One
ol the altitude
p the sedimen
ransparency o
b the water flo
ter current m
y mentioned
d that only us
ontrol the alti
of the adapta
ed in the pre
portant to rem
measure the a
tracking is a
d be within
e flow chart
nsists of 3 sta
by an altitu
p the robot
owchart.
ude Control o
m the sea sur
er column pro
a program
way is to use
e. However, t
nts on the sea
of the water
ow, causing s
measurement.
weaknesses,
ses the buoya
itude of the ro
ation of the d
evious sectio
mind here that
altitude from
active. Hence
bottom track
t of the alti
ages of predic
ude stabiliza
at the set ta
of an AUV Us
rface
ofile.
that
e the
there
abed
r. In
ome
. To
, we
ancy
obot.
depth
on to
t the
m the
, the
king
itude
ctive
ation
arget
I
unk
clos
that
be
gua
buo
spe
exp
exp
wat
of a
con
reac
F
S
dep
“Ce
min
on b
the
At f
buo
than
star
to r
set
con
incr
buo
rob
leve
dep
valu
whe
the
S
the
calc
ing Buoyancy
f we conside
known, then t
se to the seab
t the robot can
set near the
arantee that th
oyancy on tim
ed which bec
periment tim
periments, it is
ter depth from
a safe approx
nsiderably to
ch the target a
Following are
Step 1: The r
pth of the robo
ertain depth”
nimum water
board before
depth contro
first, the buoy
oyancy. After
n the neutral
rt diving. The
reduce its buo
as the minim
ntrol device,
rease again it
oyancy level.
ot should hav
el to its neutr
pth. In this ste
ue as shown i
ere L0 = 2.04
DVL sensors
Step 2: When
variable tar
culated as fol
y Control Dev
er the case w
there is a pos
bed at any m
n stop descen
neutral buoy
he robot will b
me. This has a
comes very s
me and its
s possible to g
m the GPS po
ximation of th
the reductio
altitude.
e the altitude c
robot dives w
ot reaches the
”. The “Certa
depth value.
starting the
ol with time e
yancy contro
r the buoyan
buoyancy of
e buoyancy co
oyancy level d
mum buoyanc
with maxim
ts buoyancy
The purpose
ve enough tim
ral buoyancy
ep, the target
in the followi
Dt = Dcert
m is the dista
s, At is the tar
n the robot is n
rget depth c
llows:
Dt = DCert – L
vice
where the wa
sibility that t
moment. Hen
nding the buoy
yancy value
be able to reac
direct impact
slow and then
cost. Howev
get a rough es
osition. The d
he water dept
on of the tim
control steps
with a fast sp
e depth limit
ain depth” is
. Dcert is inpu
descent. In th
estimation sch
ol device will
ncy level bec
f the robot, S
ontrol device
down up to 2
cy level of t
mum speed.
level close t
of this strate
me to change
when reachi
depth (Dt) is
ing equation:
– L0 – At
ance between
rget altitude.
near the certai
control is st
L0 + Amax – A
ater depth is
he robot gets
ce, to ensure
yancy should
in a way to
ch the neutral
t on the robot
n extends the
ver, in real
stimate of the
determination
h contributes
me needed to
:
peed until the
(Dcert) of the
s the certain
ut by the user
his first step,
heme is used.
decrease the
comes lower
OTAB-I will
will continue
0%, which is
the buoyancy
Then it will
o the neutral
egy is that the
its buoyancy
ing the target
set at a fixed
(5)
the CTD and
in depth limit
tarted. Dt is
At (6)
s
s
e
d
o
l
t
e
l
e
n
s
o
e
e
n
r
,
.
e
r
l
e
s
y
l
l
e
y
t
d
)
d
t,
s
)
After pass
that the DV
current altitu
limited up t
depth. In t
estimation is
(Dt) is set eq
range Amax
depth will c
robot decre
variable targ
of SOTAB-I
Therefore, t
buoyancy le
when reachin
result, the ro
Step 3: W
water depth
depth D m
measured by
(L0) between
Once the
to transform
control using
The wate
depth D mea
by DVL. Th
control with
Step 4: W
target depth
depth contr
control with
control prog
around 1
mechanism o
within the t
which has
reaches zero
Dep
sing the certa
VL will dete
ude (A). Ther
o the time (T
this step, th
s still being us
qual to the cu
minus the ta
continuously
ases. Hence,
get depth. At
I is already c
there will n
evel to ensure
ng the target d
obot will dive
When the DV
(Dw) can be
measured by
y DVL taking
n the two sen
Dw
water depth i
m the altitude
g the followin
Dt =
er depth Dw i
asured by CTD
is step is also
h time estimat
When the rob
h plus or min
rol method i
h time estim
gram. The de
m as a co
of the buoyan
target depth
been set on
o, the robot w
pth and Altitu
in zone limit,
ct the seabe
refore, the bu
Tr) needed to
he depth co
sed. However
urrent depth (
arget altitude
change as th
, it is a dep
this point, th
close to the n
not be much
e that the rob
depth, as show
e at a steady s
VL detects the
e calculated a
CTD and t
g in considera
nsors as shown
= D + L0 + A
is known, it b
control to an
ng equation:
= Dw – L0 – A
is defined as
D and the alti
o carried out b
tion scheme.
bot is within
nus the depth
is switched
mation to de
epth margin D
ompensation
ncy device. SO
for a certain
the timer.
will start ascen
ude Control o
, there is a cha
d and outpu
uoyancy chang
o reach the ta
ontrol with t
r, the target d
D) plus the D
(At). The ta
he depth D of
pth control w
he buoyancy l
neutral buoya
h change in
bot is able to
wn in step 2. A
speed.
e seabed, the
as the sum of
the altitude
ation the dista
n next.
A
becomes poss
equivalent d
At
s the sum of
itude A measu
by using the d
the range of
h margin Dm,
from the d
epth stabiliza
Dm is usually
in the con
OTAB-I will
n period of t
When the ti
nding.
of an AUV Us
ance
ut its
ge is
arget
time
depth
DVL
arget
f the
with
level
ancy.
the
stop
As a
e sea
f the
(A)
ance
(7)
sible
depth
(8)
f the
ured
depth
f the
, the
depth
ation
y set
ntrol
stay
ime,
imer
5.2
In
targ
min
wat
was
at le
con
F
con
reac
befo
F
dep
was
exp
the
F
Tab
Cer
Tar
Asc
BT
Dm
Der
Sm
Bn
Bm
Bdif
Berr
Tm
Fig.
ing Buoyancy
Experiments
n this experim
get altitude e
nutes before a
ter depth at th
s unknown, b
east equal to
ntrol were set
Fig. 16 shows
ntrol. It can b
ch near the s
fore ascending
From the DV
pth which was
s composed
plained in Sec
robot ascent.
Fig. 17 illustr
ble 8 Altitude
rtain depth
rget Alt.
cending timer
T min range
m
rr
ff
r
. 16 Altitude
y Control Dev
Results
ment, the rob
equal to 9 m
ascending to t
he place wher
but the water d
724 m. The
as shown in
s the experim
be observed t
seabed and fr
g.
VL data, we
s equal to 766
of 5 steps. T
ction 1. The
.
rates the detai
e control param
72
9
30
24
0.
0.
0.
62
2%
0.
0.
20
control.
vice
bot was order
m then freeze
the sea-surfac
re the robot w
depth was est
parameters o
Table 8.
ment result of
that the robot
reeze there fo
could measu
6 m. The cont
The first fou
fifth step co
ils of the pre
meters configu
24 m
m
00 s
4
.5 m
.007 m
.02 m/s
2.5%
%
.2%
.05%
0 s
145
red to go to a
e there for 5
ce. The exact
was launched
timated to be
of the altitude
f the altitude
t managed to
for 5 minutes
ure the water
trol algorithm
ur steps were
orresponds to
dictive depth
uration.
5
a
5
t
d
e
e
e
o
s
r
m
e
o
h
146
Fig. 17 Altit
control appli
713 m, whic
that the certa
the target al
that the robo
20% at a m
and maintain
the time of
robot’s verti
and the buo
below the m
buoyancy (B
Dep
(a) Dep
(b) Depth
(c)
tude control: S
ied in step 1 w
ch can be calc
ain depth is d
ltitude is equ
ot reached the
maximum vert
ned it for 17
the experime
ical speed was
oyancy was e
maximum va
Bn_Max = Bn +
pth and Altitu
pth Vs Speed
h Vs Buoyancy
Tc Vs Tr Step 1.
with a set targ
ulated using E
defined as equ
al to 9 m. It
e minimum b
tical speed eq
5 s, which e
ent. At the en
s reduced to l
equal to 61%
alue of the e
Bm = 62.5%
ude Control o
get depth equ
Eq. (10) know
ual to 724 m
can be obser
uoyancy equ
qual to 0.49
enabled to red
nd of step 1,
less than 0.15
%, which is 3
estimated neu
+ 2% = 64.5
of an AUV Us
ual to
wing
m and
rved
al to
m/s
duce
, the
m/s
3.5%
utral
%).
Fig.
At t
cha
the
F
with
did
be s
altit
con
con
A
and
ing Buoyancy
. 18 Altitude
that buoyancy
ange to reach
robot detects
Fig. 18 illustra
h variable tar
not detect the
sure that the
tude. In this
nstant. As a
nstant and equ
At 742 m wat
d the 3rd step
y Control Dev
(a) Depth V
(b) Depth Vs B
(c) Tc V
control: Step 2
y value, the b
the neutral b
s the seabed.
ates the result
rget depth. At
e seabed, it de
robot will be
s step, the ro
consequence
ual to 0.14 m/
ter depth, the
was activate
vice
Vs Speed
Buoyancy
Vs Tr
2.
buoyancy dev
buoyancy on
ts of the predi
t this step, sin
escends slowl
e able to stop
obot buoyanc
, the robot s
/s.
robot detecte
ed. The target
vice is able to
time in case
ictive control
nce the robot
ly in a way to
p at the target
cy is almost
speed is also
ed the seabed
t altitude was
o
e
l
t
o
t
t
o
d
s
transformed
As shown
program suc
target depth
a value of bu
To freeze
stabilizer a
implementat
robot succee
set target dep
Fig. 21 ill
The maximu
Fig. 19 Altit
Dep
to an equiva
in Fig. 19,
cceeded to sm
with a vertic
uoyancy very
e the robot a
algorithm is
tion is shown
eded to keep i
pth.
lustrates the r
um speed reac
(a) Dep
(b) Depth
(c)
tude control: S
pth and Altitu
alent target de
the predictiv
moothly reach
al speed almo
close to the n
at the target
used. The
n in Fig. 20.
its depth with
robot ascent t
ched was 0.3
pth Vs Speed
h Vs Buoyancy
Tc Vs Tr
Step 3.
ude Control o
epth Dt = 755
ve depth con
h the robot at
ost equal to 0
neutral buoya
altitude, a d
e result of
It shows that
hin (+/-) 1 m f
o the sea surf
9 m/s.
of an AUV Us
5 m.
ntrol
t the
0 and
ancy.
depth
f its
t the
from
face.
Fig.
Fig.
ing Buoyancy
. 20 Altitude
. 21 Altitude
y Control Dev
(a) Depth V
(b) Depth Vs B
control: Step 4
(a) Depth V
(b) Depth Vs B
control: Step 5
vice
Vs Speed
Buoyancy 4.
Vs Speed
Buoyancy
5.
1477
Depth and Altitude Control of an AUV Using Buoyancy Control Device
148
In summary, the 3 stages of predictive depth control
succeeded to bring the robot to the target altitude
with a buoyancy value close to the neutral and with
vertical speed almost equal to 0. Besides, the altitude
stabilizer succeeded to maintain the robot within 1 m
from the target altitude. The definition of the certain
depth helped to reduce the time to reach the target
altitude.
6. Conclusions
A new method for depth control using the buoyancy
control device was developed. A model of the
buoyancy variation with time was established. It was
built based on the results obtained in high pressure tank
experiment and several at-sea experiments. The depth
control algorithm is based on the comparison between
the time estimated for the robot to change its buoyancy
from its current value to the neutral value, and the time
expected for the robot to reach the target depth. The
method was demonstrated at-sea experiments in
Toyama Bay in Japan in March 2016. It showed the
ability of the control algorithm to smoothly bring
the robot to the target depth without a significant
overshoot. The algorithm is characterized by its
flexibility and does not require a strict determination
neutral buoyancy value. A margin of inaccuracy can be
customized before performing the dive. The method
could be further adapted to perform an altitude control
through a progressive depth control algorithm based on
4 steps. The experiment results showed that it worked
properly.
Acknowledgements
This research project was funded for
2011FY-2015FY by Grant-in-Aid for Scientific
Research(S) of Japan Society for the Promotion of
Science (No. 23226017).
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