I
nte
rna
t
io
na
l
J
o
urna
l
of
Ro
bo
t
ics
a
nd
Aut
o
m
a
t
io
n
(
I
J
R
A)
Vo
l.
9
,
No
.
4
,
Dec
em
b
er
2
0
2
0
,
pp.
2
7
1
~2
8
0
I
SS
N:
2089
-
4
8
5
6
,
DOI
:
1
0
.
1
1
5
9
1
/
i
jr
a
.
v9
i
4
.
pp
2
7
1
-
2
8
0
271
J
o
ur
na
l
ho
m
ep
a
g
e
:
h
ttp
:
//ij
r
a
.
ia
esco
r
e.
co
m
The
a
lg
o
rithm
of
a
da
ptive
co
ntrol
f
o
r
a
ctive
sus
pensi
o
n
sy
stems
using
po
le
a
ss
ig
n
a
nd
ca
sca
de
desig
n
met
ho
d
Chi
Ng
uy
en
Va
n
Th
a
i
Ng
u
y
e
n
Un
i
v
e
rsity
of
Tec
h
n
o
lo
g
y
,
Vie
tn
a
m
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Mar
11
,
20
20
R
ev
is
ed
May
31
,
20
20
Acc
ep
ted
Sep
10
,
20
20
Th
is
p
a
p
e
r
p
re
se
n
ts
th
e
a
c
ti
v
e
su
s
p
e
n
sio
n
sy
ste
m
(ASS
)
c
o
n
tro
l
m
e
th
o
d
u
si
n
g
th
e
a
d
a
p
ti
v
e
c
a
sc
a
d
e
c
o
n
tr
o
l
sc
h
e
m
e
.
Th
e
c
o
n
tro
l
sc
h
e
m
e
is
imp
le
m
e
n
ted
by
two
c
o
n
tr
o
l
lo
o
p
s,
th
e
i
n
n
e
r
c
o
n
tr
o
l
lo
o
p
a
n
d
o
u
ter
c
o
n
tro
l
l
o
o
p
a
r
e
d
e
sig
n
e
d
re
sp
e
c
ti
v
e
ly
.
Th
e
in
n
e
r
c
o
n
tr
o
l
lo
o
p
u
se
s
th
e
p
o
le
a
ss
ig
n
m
e
n
t
m
e
th
o
d
in
o
rd
e
r
to
m
o
v
e
th
e
p
o
les
of
t
h
e
o
rig
i
n
a
l
sy
ste
m
to
d
e
sire
d
p
o
les
re
sp
e
c
t
to
th
e
re
q
u
ire
d
p
e
rf
o
rm
a
n
c
e
of
th
e
s
u
sp
e
n
sio
n
sy
ste
m
.
To
d
e
si
g
n
t
h
e
c
o
n
tro
ll
e
r
in
t
h
e
in
n
e
r
lo
o
p
,
th
e
m
o
d
e
l
wit
h
o
u
t
th
e
n
o
ise
c
a
u
se
d
by
t
h
e
ro
a
d
p
ro
fil
e
a
n
d
v
e
lo
c
it
y
of
t
h
e
car
is
u
se
d
.
Th
e
o
u
ter
c
o
n
tro
l
l
o
o
p
t
h
e
n
d
e
sig
n
e
d
wit
h
an
a
d
a
p
ti
v
e
m
e
c
h
a
n
ism
c
a
lcu
late
s
t
h
e
a
c
ti
v
e
c
o
n
tro
l
fo
rc
e
to
c
o
m
p
e
n
sa
te
fo
r
th
e
v
i
b
ra
ti
o
n
s
c
a
u
se
d
by
t
h
e
r
o
a
d
p
ro
fil
e
a
n
d
v
e
lo
c
it
y
of
t
h
e
c
a
r.
T
h
e
c
o
n
tro
l
fo
rc
e
is
d
e
term
in
e
d
by
th
e
e
rr
o
r
b
e
twe
e
n
sta
tes
of
th
e
re
fe
re
n
c
e
m
o
d
e
l
a
n
d
sta
tes
of
su
sp
e
n
sio
n
sy
ste
m
s,
th
e
re
fe
re
n
c
e
m
o
d
e
l
is
th
e
m
o
d
e
l
of
c
lo
se
d
lo
o
p
with
i
n
n
e
r
c
o
n
tr
o
l
lo
o
p
with
o
u
t
th
e
n
o
i
se
.
T
h
e
sim
u
lati
o
n
re
su
lt
s
imp
lem
e
n
ted
by
u
sin
g
t
h
e
p
ra
c
ti
c
e
d
a
te
of
t
h
e
ro
a
d
p
ro
fil
e
sh
o
w
t
h
a
t
th
e
c
a
p
a
b
il
it
y
of
o
sc
il
lati
o
n
d
e
c
re
a
se
fo
r
ASS
is
q
u
it
e
e
fficie
n
t.
K
ey
w
o
r
d
s
:
Ad
ap
tiv
e
co
n
tr
o
l
C
ascad
e
co
n
tr
o
l
Po
le
ass
ig
n
m
en
t
m
eth
o
d
R
o
ad
ex
citatio
n
R
o
ad
p
r
o
f
ile
Su
s
p
en
s
io
n
s
y
s
tem
T
h
is
is
an
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r
th
e
CC
BY
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
C
h
i
Ng
u
y
en
Van
,
Dep
ar
tm
en
t
of
C
o
n
tr
o
l
E
n
g
in
e
er
in
g
an
d
I
n
s
tr
u
m
en
ts
,
T
h
ai
Ng
u
y
e
n
Un
iv
er
s
ity
of
T
e
ch
n
o
lo
g
y
,
3
/2
S
tr
ee
t,
T
h
ai
Ng
u
y
en
C
ity
,
Viet
Nam
.
E
m
ail:
n
g
ch
i@
tn
u
t.e
d
u
.
v
n
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
m
ain
ad
v
a
n
tag
e
of
th
e
ac
tiv
e
s
u
s
p
en
s
io
n
s
y
s
tem
(
ASS)
is
th
e
ca
p
ab
ilit
y
of
ch
an
g
in
g
th
e
d
y
n
am
ic
wh
ee
l
lo
a
d
(
Fd
y
n
)
in
o
r
d
er
to
im
p
r
o
v
e
th
e
r
id
e
co
m
f
o
r
t
f
o
r
p
ass
en
g
er
s
by
ad
ju
s
tin
g
th
e
ch
ar
ac
ter
is
tic
of
a
s
u
s
p
en
s
io
n
s
y
s
tem
lik
e
th
e
s
tiff
n
ess
,
th
e
d
am
p
in
g
.
T
h
e
elec
tr
o
m
ag
n
etic,
h
y
d
r
a
u
lic
ac
tu
ato
r
s
m
o
s
tly
ar
e
u
s
ed
to
g
en
er
ate
th
e
ac
tiv
e
f
o
r
ce
in
th
e
ASS.
T
h
e
co
n
tr
o
l
p
r
o
b
lem
f
o
r
ASS
is
alwa
y
s
m
o
r
e
ch
allen
g
in
g
f
o
r
r
esear
ch
in
g
an
d
ap
p
licatio
n
in
th
e
p
r
ac
tice
b
ec
a
u
s
e
of
s
o
m
e
r
ea
s
o
n
s
[
1
,
2
]
:
th
er
e
ar
e
m
an
y
ASS’s
s
ta
tes
n
ee
d
to
be
co
n
tr
o
lled
wh
ile
ASS
h
a
s
o
n
ly
one
co
n
tr
o
l
in
p
u
t,
th
e
c
o
n
tr
o
lled
ac
tiv
e
f
o
r
ce
ac
ts
co
n
tem
p
o
r
an
e
o
u
s
ly
on
b
o
th
s
p
r
u
n
g
m
ass
an
d
s
p
r
u
n
g
m
ass
,
th
e
p
er
f
o
r
m
an
ce
b
an
d
w
id
th
of
ac
t
u
ato
r
is
lim
ited
,
t
h
e
lim
itatio
n
s
of
tim
e,
th
e
r
esp
o
n
s
e
tim
e
d
o
es
not
m
ee
t
th
e
r
eq
u
ir
em
e
n
t
of
h
i
g
h
v
elo
city
,
all
ASS’s
s
tate
s
ar
e
not
m
ea
s
u
r
ed
by
s
en
s
o
r
s
,
th
e
d
eter
m
in
in
g
s
tatis
tic
ch
ar
ac
ter
is
tics
of
r
o
ad
e
x
citatio
n
is
th
e
p
r
ac
tice
d
if
f
icu
lty
.
T
h
er
e
ar
e
lo
ts
of
co
n
tr
o
l
m
et
h
o
d
s
f
o
r
ASS
in
clu
d
in
g
:
in
th
e
m
ater
ial
[
3
]
,
th
e
au
th
o
r
s
u
s
ed
th
e
s
elf
-
lear
n
in
g
n
e
u
r
al
n
etwo
r
k
s
to
ad
ju
s
t
co
n
tr
o
ller
p
ar
am
eter
s
in
o
r
d
er
to
im
p
r
o
v
e
th
e
r
id
e
co
m
f
o
r
t,
th
e
co
m
p
lex
ity
of
n
eu
r
al
n
etwo
r
k
s
an
d
ca
p
ab
i
liti
es
of
co
n
v
er
g
e
n
ce
ar
e
th
e
d
is
ad
v
an
tag
es
of
th
is
m
eth
o
d
.
Usi
n
g
th
e
Sk
y
h
o
o
k
r
ef
er
en
ce
m
o
d
el
a
n
d
th
e
ad
ap
tiv
e
p
ar
am
eter
c
o
n
tr
o
ller
b
ase
d
on
t
h
e
L
y
a
p
u
n
o
v
m
eth
o
d
is
p
r
esen
ted
in
[
4
]
.
In
[
5
,
6
]
,
au
th
o
r
s
a
p
p
lied
th
e
f
r
ee
-
m
o
d
el
s
lid
in
g
mode
c
o
n
tr
o
l
with
tim
e
-
d
ela
y
esti
m
atio
n
to
elim
in
ate
th
e
n
o
n
lin
ea
r
,
u
n
ce
r
tain
ty
an
d
n
o
is
e
ac
tin
g
on
th
e
s
y
s
tem
.
T
h
e
m
o
d
al
f
ee
d
b
ac
k
m
et
h
o
d
u
s
e
d
to
co
n
tr
o
l
ASS
is
wr
itten
in
th
e
m
ater
ial
[
7
]
,
th
i
s
m
eth
o
d
co
n
tr
o
l
in
d
ep
en
d
en
t
ly
in
each
v
ib
r
atio
n
mode
of
ASS,
th
e
co
n
tr
o
ller
p
ar
am
eter
s
ar
e
tu
r
n
ed
by
an
o
p
tim
al
co
n
tr
o
l
m
eth
o
d
.
Usi
n
g
s
ec
o
n
d
o
r
d
er
o
p
tim
al
L
QG
co
n
tr
o
ller
f
o
r
ASS
is
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4
8
5
6
I
nt
J
R
ob
&
A
u
to
m
,
Vo
l.
9
,
N
o
.
4
,
Dec
em
b
er
2
0
2
0
:
2
7
1
–
280
272
co
n
d
u
cte
d
in
th
e
[
8
]
,
in
wh
ich
th
e
ASS
m
o
d
el
is
r
ewr
itten
in
th
e
lin
ea
r
f
o
r
m
.
In
th
e
ar
ticle
[
9
]
,
th
e
co
n
tr
o
ller
b
ased
on
b
ac
k
s
tep
p
in
g
m
eth
o
d
is
u
s
ed
to
c
o
n
tr
o
l
ASS,
in
t
h
is
m
eth
o
d
c
o
n
tr
o
l
law
is
d
esig
n
ed
to
b
ac
k
s
tep
f
r
o
m
in
n
er
lo
o
p
to
o
u
ter
lo
o
p
by
u
s
in
g
th
e
v
ir
tu
al
co
n
tr
o
l
i
n
p
u
ts
.
T
h
e
s
im
p
le
d
ec
o
u
p
lin
g
m
eth
o
d
f
o
r
ASS
is
im
p
lem
en
ted
by
th
e
au
th
o
r
s
of
[
1
0
]
.
Mo
r
e
o
v
er
,
th
e
r
e
ar
e
lo
ts
of
co
n
tr
o
l
m
eth
o
d
s
ap
p
lied
to
ASS
in
clu
d
in
g
th
e
E
v
en
t
-
tr
ig
g
e
r
ed
co
n
tr
o
l
[
1
1
]
,
H∞
co
n
tr
o
l
m
eth
o
d
u
s
in
g
th
e
L
in
ea
r
m
atr
ix
in
e
q
u
ality
,
th
e
f
u
zz
y
lo
g
ic
co
n
tr
o
l
m
eth
o
d
[
1
2
]
,
etc.
T
h
e
co
m
m
o
n
f
ea
tu
r
e
of
t
h
e
ab
o
v
e
m
eth
o
d
s
is
th
e
n
o
is
e
c
au
s
ed
by
r
o
ad
p
r
o
f
ile
co
n
s
id
er
ed
to
be
th
e
m
ain
n
o
is
e
in
p
u
t
of
th
e
m
ath
em
atica
l
m
o
d
el,
th
is
m
o
d
el
is
not
co
n
ce
r
n
ab
o
u
t
th
at
n
o
is
e
wh
ich
is
d
ep
en
d
on
th
e
r
o
ad
p
r
o
f
ile
an
d
v
elo
c
ity
of
th
e
ca
r
.
In
t
h
is
p
ap
er
,
we
u
s
e
th
e
g
e
n
er
al
m
o
d
el
of
ASS,
in
th
at
m
o
d
el
th
e
p
ar
a
m
eter
s
r
elate
d
to
t
h
e
n
o
is
e
ca
u
s
ed
by
r
o
ad
p
r
o
f
il
e
an
d
v
elo
city
of
th
e
car
ar
e
co
n
s
id
er
e
d
.
Fr
o
m
th
e
p
r
ac
tice
test
,
we
s
ee
th
at
t
h
e
f
aster
v
elo
city
of
th
e
car
is
th
e
s
m
all
am
p
litu
d
e
of
t
h
e
n
o
is
e
is
an
d
th
e
f
aster
f
r
eq
u
e
n
cy
is
.
T
h
is
f
ea
tu
r
e
m
a
k
es
th
e
n
o
is
e
ch
ar
ac
ter
is
tic
ac
tin
g
to
t
h
e
ASS
ch
an
g
e.
B
ased
on
th
at
m
o
d
el
of
ASS,
th
e
co
n
tr
o
l
p
r
o
ce
s
s
f
o
r
ASS
is
im
p
lem
en
ted
by
two
co
n
tr
o
l
lo
o
p
s
.
T
h
e
in
n
e
r
co
n
tr
o
l
lo
o
p
is
d
esig
n
ed
with
n
o
is
es
with
o
u
t
a
f
f
ec
tin
g
ASS,
th
is
co
n
tr
o
l
lo
o
p
d
r
iv
es
th
e
p
er
f
o
r
m
a
n
ce
of
ASS
in
t
h
e
tr
an
s
ien
t
p
e
r
io
d
.
T
h
e
m
o
d
el
of
clo
s
ed
l
o
o
p
s
y
s
tem
with
in
n
er
co
n
tr
o
l
lo
o
p
is
u
s
ed
as
r
e
f
er
en
ce
m
o
d
e
l
f
o
r
t
h
e
d
esig
n
i
n
g
th
e
o
u
ter
ad
a
p
tiv
e
c
o
n
tr
o
l
lo
o
p
.
T
h
e
r
ef
e
r
en
ce
m
o
d
el
d
ep
e
n
d
s
on
th
e
v
elo
city
of
t
h
e
ca
r
.
T
h
e
o
u
ter
a
d
ap
tiv
e
co
n
tr
o
l
l
o
o
p
u
s
es
th
e
p
ar
am
et
er
ad
ap
tiv
e
m
ec
h
a
n
is
m
ad
ju
s
t
ed
by
th
e
v
elo
city
of
th
e
car
an
d
er
r
o
r
s
b
etwe
en
ASS’s
s
tates
an
d
s
tates
of
th
e
r
ef
er
en
ce
m
o
d
el.
T
h
e
ad
ap
tiv
e
f
o
r
ce
is
g
en
er
ated
to
co
m
p
e
n
s
ate
f
o
r
th
e
ab
o
v
e
er
r
o
r
s
in
o
r
d
e
r
to
d
r
iv
e
t
h
at
er
r
o
r
r
ea
ch
in
g
to
ze
r
o
.
T
h
e
s
im
u
latio
n
r
esu
lts
u
s
in
g
th
e
p
r
ac
tice
r
o
ad
p
r
o
f
ile
s
h
o
w
th
at
th
is
m
eth
o
d
is
ef
f
ic
ien
t
to
ap
p
l
y
to
t
h
e
p
r
ac
tice.
T
h
e
r
em
ain
i
n
g
p
ar
t
of
th
is
p
a
p
er
is
s
tr
u
ctu
r
ed
as
f
o
llo
ws:
Par
t
two
m
en
tio
n
s
t
h
e
m
o
d
elin
g
of
th
e
s
u
s
p
en
s
io
n
s
y
s
tem
.
Par
t
th
r
ee
in
tr
o
d
u
ce
s
ad
ap
tiv
e
co
n
tr
o
l
f
o
r
th
e
ASS
.
Par
t
f
o
u
r
s
h
o
ws
t
h
e
s
im
u
latio
n
r
esu
lts
.
Fin
ally
,
p
ar
t
f
iv
e
s
u
m
m
a
r
izes
s
o
m
e
co
n
clu
s
io
n
s
.
2.
M
AIN
CO
N
T
E
NT
S
2
.
1
.
M
o
dellin
g
of
t
he
ASS
T
h
e
ac
tiv
e
s
u
s
p
en
s
io
n
d
ep
ic
ted
in
Fig
u
r
e
1
s
y
s
tem
co
n
s
is
t
s
of
s
p
r
u
n
g
m
ass
an
d
u
n
s
p
r
u
n
g
m
ass
,
th
e
s
p
r
u
n
g
m
ass
,
an
d
u
n
s
p
r
u
n
g
m
ass
ar
e
co
n
n
ec
ted
by
th
e
s
u
s
p
en
s
io
n
p
ar
t
in
clu
d
in
g
d
am
p
i
n
g
p
ar
t
an
d
s
p
r
in
g
p
ar
t
in
p
a
r
allel
[
13
].
In
ca
s
e
of
ac
tiv
e
s
u
s
p
en
s
io
n
,
th
e
ac
tiv
e
ac
t
u
ato
r
(
elec
tr
ical
,
elec
tr
o
m
ag
n
etic,
h
y
d
r
ic
d
ev
ic
es
d
r
iv
en
by
elec
tr
ical
s
ig
n
al
(
)
)
is
ad
d
ed
to
th
is
p
ar
t
to
ch
an
g
e
th
e
n
atu
r
al
ch
ar
ac
ter
is
tics
of
s
u
s
p
en
s
io
n
p
ar
t
in
o
r
d
er
to
g
et
th
e
d
esire
d
co
m
f
o
r
t
r
id
e.
T
h
e
co
n
n
ec
tio
n
b
etwe
en
th
e
u
n
s
p
r
u
n
g
m
ass
an
d
th
e
r
o
ad
s
u
r
f
ac
e
is
th
e
wh
ee
l.
T
h
e
wh
ee
l
is
d
escr
ib
ed
by
wh
ee
l
d
am
p
in
g
p
ar
t
an
d
wh
ee
l
s
p
r
in
g
p
ar
t
.
T
h
e
s
tates
of
th
e
s
u
s
p
en
s
io
n
s
y
s
tem
ar
e
d
ef
lectio
n
,
v
el
o
city
,
an
d
ac
ce
l
er
ato
r
of
s
p
r
u
n
g
m
ass
,
̇
,
̈
,
u
n
s
p
r
u
n
g
m
ass
,
̇
̈
,
r
esp
ec
tiv
ely
.
T
h
e
is
th
e
r
o
ad
ex
citatio
n
s
u
p
p
o
r
ted
as
th
e
m
ain
in
p
u
t
n
o
is
e
of
th
e
s
y
s
tem
,
d
ep
e
n
d
s
on
th
e
r
o
ad
p
r
o
f
ile
an
d
v
el
o
city
of
th
e
car
(
)
.
T
h
e
p
er
f
o
r
m
an
ce
q
u
ality
of
th
e
s
u
s
p
en
s
io
n
s
y
s
tem
is
r
ef
lecte
d
u
p
o
n
th
e
co
m
f
o
r
t
r
id
e,
th
is
q
u
ality
is
p
r
esen
ted
by
3
p
a
r
am
eter
s
:
th
e
ac
ce
ler
atio
n
s
of
th
e
car
an
d
th
e
wh
ee
l
̈
,
̈
r
esp
ec
tiv
ely
,
th
e
d
y
n
am
ic
wh
ee
l
lo
ad
an
d
th
e
s
u
s
p
en
s
io
n
d
e
f
lectio
n
−
.
T
h
e
d
y
n
a
m
ic
wh
ee
l
lo
ad
is
ca
lcu
lated
as
(
1
)
as
[1
4
]
.
=
(
−
)
+
(
̇
−
̇
)
(
1
)
Fig
u
r
e
1.
Ph
y
s
ical
m
o
d
el
of
a
ty
p
ical
s
u
s
p
en
s
io
n
s
y
s
tem
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
R
ob
&
A
u
to
m
I
SS
N:
2089
-
4
8
5
6
Th
e
a
lg
o
r
ith
m
of
a
d
a
p
tive
co
n
tr
o
l
fo
r
a
ctive
s
u
s
p
en
s
io
n
s
yst
ems
u
s
in
g
p
o
le
a
s
s
ig
n
...
(
C
h
i
N
g
u
ye
n
V
a
n
)
273
T
h
e
d
y
n
am
ic
wh
ee
l
lo
a
d
d
ep
en
d
s
on
th
e
m
ass
of
th
e
ca
r
v
elo
city
of
th
e
car
(
)
an
d
r
o
a
d
p
r
o
f
ile.
T
h
e
s
m
aller
v
alu
es
of
̈
,
̈
,
ar
e,
th
e
h
ig
h
er
c
o
m
f
o
r
t
r
id
er
of
th
e
p
ass
en
g
e
r
s
in
th
e
car
is
Fig
u
r
e
1.
T
h
e
r
o
ad
e
x
citatio
n
alwa
y
s
is
s
u
p
p
o
s
ed
as
th
e
m
ain
in
p
u
t
n
o
is
e,
but
we
r
ea
lize
th
at
th
e
not
o
n
ly
d
e
p
en
d
s
on
th
e
r
o
ad
p
r
o
f
ile
b
u
t
also
th
e
v
elo
city
of
th
e
ca
r
.
Fo
r
th
e
s
am
e
r
o
ad
p
r
o
f
ile,
as
th
e
v
elo
city
of
th
e
car
ch
a
n
g
es,
th
e
s
to
ch
asti
c
ch
ar
ac
ter
is
tics
of
th
e
will
be
ch
an
g
ed
.
Fig
u
r
e
2
s
h
o
ws
th
e
v
ar
y
in
g
of
th
e
in
th
e
ca
s
e
v
elo
city
of
th
e
car
ch
an
g
in
g
f
r
o
m
5
k
m
/h
to
45
k
m
/h
f
o
r
th
e
s
am
e
r
o
ad
p
r
o
f
ile.
T
h
e
r
o
ad
p
r
o
f
ile
h
as
th
e
s
to
ch
asti
c
ch
ar
ac
ter
is
tic
s
:
=
−
2
.
319
,
=
2
.
348
,
=
0
.
0131
,
=
0
.
0131
;
=
0
.
331678
,
=
0
.
0131
,
=
0
.
576
.
Fro
m
F
ig
u
r
e
3
we
s
ee
th
at
th
e
v
elo
city
of
th
e
ca
r
is
h
ig
h
er
,
th
e
am
p
litu
d
e
of
th
e
v
a
r
iatio
n
is
lo
wer
.
T
h
e
m
ax
im
u
m
of
is
0
.
0
7
y
m
in
th
e
ca
s
e
(
)
=
5
/
ℎ
,
th
e
m
ax
im
u
m
s
of
ar
e
0
.
023
an
d
0
.
02
in
th
e
ca
s
es
(
)
=
15
/
ℎ
an
d
45
/
ℎ
,
r
esp
ec
tiv
ely
.
T
h
e
ch
an
g
in
g
of
s
to
ch
asti
c
ch
ar
ac
ter
is
tics
by
th
e
v
elo
city
of
t
h
e
ca
r
,
t
h
e
r
o
a
d
p
r
o
f
ile
will
af
f
ec
t
s
tr
o
n
g
ly
to
th
e
s
tate
esti
m
atio
n
p
r
o
ce
s
s
.
T
h
e
f
ir
s
t
o
r
d
er
m
o
d
el
of
t
h
e
r
o
ad
e
x
citatio
n
as
th
e
f
u
n
ctio
n
of
th
e
r
o
a
d
p
r
o
f
ile
a
n
d
v
elo
city
of
th
e
car
d
e
p
icted
in
Fig
u
r
e
4
c
an
be
wr
itten
by
th
e
e
q
u
atio
n
as
[
1
5
,
16
]
:
=
−
(
)
+
(
2
)
w
h
er
e
,
ar
e
th
e
o
p
tio
n
al
f
ee
d
b
a
ck
p
ar
am
eter
a
n
d
v
elo
city
of
th
e
ca
r
,
r
esp
ec
tiv
ely
,
is
th
e
in
p
u
t
n
o
is
e
ca
u
s
ed
by
th
e
r
o
a
d
p
r
o
f
ile.
L
et
co
n
s
id
er
th
e
s
tate
v
ec
to
r
of
th
e
s
u
s
p
en
s
io
n
s
y
s
tem
d
escr
i
b
ed
in
Fig
u
r
e
1
as
:
1
=
,
2
=
̇
,
3
=
,
4
=
̇
,
5
=
,
6
=
̇
=
[
1
2
3
4
5
6
]
(
3
)
Su
p
p
o
s
e
(
)
as
th
e
ac
tiv
e
f
o
r
ce
,
if
(
)
=
0
s
y
s
tem
is
ca
lled
th
e
p
ass
iv
e
s
u
s
p
en
s
io
n
s
y
s
tem
.
T
h
e
m
o
d
el
of
th
e
s
u
s
p
en
s
io
n
s
y
s
tem
is
wr
itten
by
t
h
e
f
o
llo
win
g
eq
u
atio
n
.
=
(
(
)
)
+
(
)
+
(
t
)
(
4
)
wh
er
e
≜
[
0
1
0
0
0
0
−
−
0
0
0
0
0
1
0
0
−
−
−
−
−
(
)
0
0
0
0
0
0
1
0
0
0
0
−
(
)
0
]
,
≜
[
0
1
0
−
1
0
0
]
,
(
)
=
[
]
(
5
)
By
m
o
d
if
y
in
g
th
e
(
5
)
as
=
(
(
)
)
+
̃
[
(
)
+
(
)
]
(
6
)
w
ith
̃
=
[
]
,
(
)
=
(
(
)
)
,
(
)
=
[
0
(
)
]
,
=
6
(
7
)
th
e
s
y
s
tem
h
as
th
e
in
p
u
t
(
)
(
)
=
(
(
)
)
(
)
=
[
1
]
(
)
(
8
)
Ma
tr
ix
(
(
)
)
h
as
s
ix
eig
en
v
alu
es
lo
c
ated
in
t
h
e
lef
t
of
t
h
e
im
a
g
in
a
r
y
ax
is
wh
ic
h
m
a
k
e
03
p
air
s
of
eig
en
v
alu
es
th
at
a
r
e
s
y
m
m
etr
ic
with
r
esp
ec
t
to
th
e
im
ag
in
ar
y
ax
is
.
T
wo
f
ir
s
t
of
th
em
ar
e
f
ix
ed
an
d
h
av
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4
8
5
6
I
nt
J
R
ob
&
A
u
to
m
,
Vo
l.
9
,
N
o
.
4
,
Dec
em
b
er
2
0
2
0
:
2
7
1
–
280
274
th
e
n
eg
ativ
e
r
ea
l
p
ar
t,
th
e
las
t
p
air
d
e
p
en
d
s
on
th
e
v
elo
cit
y
of
t
h
e
ca
r
.
T
h
e
v
elo
city
of
th
e
car
i
n
cr
ea
s
in
g
m
ak
es
th
e
im
ag
in
ar
y
p
ar
t
of
t
h
e
th
ir
d
p
ai
r
of
eig
e
n
v
alu
es
m
o
v
e
alo
n
g
th
e
im
ag
in
a
r
y
ax
is
f
ar
f
r
o
m
th
e
r
o
o
t
as
d
escr
ib
ed
in
th
e
Fig
u
r
e
3
.
Fig
u
r
e
2.
T
h
e
v
ar
y
in
g
of
th
e
s
to
ch
asti
c
ch
ar
ac
ter
is
tics
f
o
r
th
e
s
am
e
r
o
ad
p
r
o
f
ile
by
th
e
v
elo
city
of
th
e
car
Fig
u
r
e
3.
T
h
e
lo
ca
tio
n
s
of
p
o
le
p
air
s
of
th
e
ASS
Fig
u
r
e
4.
T
h
e
f
ir
s
t
o
r
d
er
m
o
d
e
l
of
r
o
a
d
ex
citatio
n
z
r
as
th
e
f
u
n
ctio
n
of
th
e
r
o
a
d
p
r
o
f
i
le
an
d
v
el
o
city
of
t
h
e
car
2
.
2
.
Ada
ptiv
e
co
ntr
o
l
f
o
r
t
he
ASS
T
h
e
ad
ap
tiv
e
c
o
n
tr
o
l
f
o
r
ASS
is
d
esig
n
ed
by
two
s
tep
s
as
f
o
l
lo
ws.
-
Ste
p
1:
Desig
n
th
e
s
tate
f
e
ed
b
ac
k
c
o
n
tr
o
ller
in
o
r
d
er
to
k
ee
p
clo
s
ed
lo
o
p
s
y
s
tem
with
o
u
t
n
o
is
e
(
)
=
0
h
av
in
g
th
e
d
esire
d
d
y
n
am
ic.
T
h
e
p
o
le
p
lace
m
e
n
t
is
th
e
tech
n
iq
u
e
th
at
is
u
s
ed
to
p
lace
th
e
c
lo
s
ed
lo
o
p
p
o
les
of
th
e
s
y
s
tem
in
p
r
ed
eter
m
in
e
d
lo
ca
tio
n
s
.
B
ased
on
th
e
d
esire
d
d
y
n
am
ic
wh
ee
l
lo
ad
an
d
th
e
d
esire
d
d
y
n
am
ic
of
,
̇
th
e
p
r
ed
eter
m
in
ed
lo
ca
tio
n
s
of
t
h
e
p
o
les
ar
e
ca
lcu
lated
.
T
h
e
r
e
s
u
lts
of
S
tep
1
is
th
e
s
tate
f
ee
d
b
ac
k
co
n
tr
o
ller
wh
ich
h
as
th
e
g
ai
n
d
ep
en
d
in
g
on
th
e
v
elo
city
of
th
e
car
a
n
d
th
e
r
o
ad
p
r
o
f
ile.
T
h
is
is
th
e
in
n
er
co
n
t
r
o
l
lo
o
p
.
-
Ste
p
2:
Desig
n
th
e
ad
a
p
tiv
e
c
o
n
tr
o
ller
in
th
e
o
u
ter
co
n
t
r
o
l
l
o
o
p
to
atte
n
u
ate
th
e
n
o
is
e
ca
u
s
ed
by
th
e
r
o
ad
p
r
o
f
ile
an
d
v
elo
city
of
th
e
ca
r
.
T
h
is
c
o
n
tr
o
l
lo
o
p
u
s
es
th
e
r
e
f
er
en
ce
m
o
d
el
to
be
th
e
m
o
d
e
l
of
in
n
er
lo
o
p
with
o
u
t
n
o
is
e
(
)
,
th
e
d
y
n
am
ic
of
th
e
r
e
f
er
en
ce
m
o
d
el
is
d
ep
e
n
d
ed
on
th
e
v
elo
city
of
th
e
car
an
d
r
o
a
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
R
ob
&
A
u
to
m
I
SS
N:
2089
-
4
8
5
6
Th
e
a
lg
o
r
ith
m
of
a
d
a
p
tive
co
n
tr
o
l
fo
r
a
ctive
s
u
s
p
en
s
io
n
s
yst
ems
u
s
in
g
p
o
le
a
s
s
ig
n
...
(
C
h
i
N
g
u
ye
n
V
a
n
)
275
p
r
o
f
ile.
Usi
n
g
s
tate
er
r
o
r
b
et
wee
n
th
e
ASS
an
d
r
ef
er
en
ce
m
o
d
el,
t
h
e
ad
a
p
tiv
e
m
ec
h
a
n
is
m
ca
lcu
lates
th
e
ac
tiv
e
f
o
r
ce
to
co
m
p
en
s
a
te
f
o
r
th
e
n
o
is
e
ca
u
s
ed
by
t
h
e
r
o
ad
p
r
o
f
ile
an
d
v
elo
city
of
th
e
ca
r
.
T
h
e
ad
ap
tiv
e
m
ec
h
a
n
is
m
g
ain
is
v
a
r
ied
r
o
a
d
co
n
d
itio
n
an
d
v
elo
cit
y
of
th
e
ca
r
.
2
.
2
.
1
.
Desig
nin
g
t
he
inn
er
co
ntr
o
l
lo
o
p
To
d
esig
n
th
e
c
o
n
tr
o
ller
in
t
h
e
in
n
er
co
n
tr
o
l
lo
o
p
we
s
u
p
p
o
s
e
th
at
th
e
v
elo
city
of
t
h
e
c
ar
is
ze
r
o
,
so
(
)
=
0
or
(
)
=
+
1
.
C
o
n
s
id
er
th
at
all
s
tates
of
ASS
(
)
ar
e
m
ea
s
u
r
ab
le.
T
h
er
e
f
o
r
e,
th
e
m
o
d
el
of
ASS
can
be
wr
itten
as
(
7
)
:
=
(
(
)
)
+
̃
(
)
(
9
)
So
th
e
d
esig
n
i
n
g
is
to
d
et
er
m
in
e
th
e
m
atr
ix
(
(
)
)
to
g
u
a
r
an
t
ee
th
at
(
)
=
(
)
+
(
(
)
)
m
ak
es
th
e
m
o
d
el
of
clo
s
ed
-
lo
o
p
s
y
s
te
m
b
ec
o
m
e
=
(
(
(
)
)
−
̃
(
(
)
)
)
+
̃
(
)
=
̃
(
(
)
)
+
̃
(
)
(
10
)
an
d
th
e
p
o
les
of
th
e
d
y
n
am
ic
s
y
s
tem
(
8
)
1
,
2
,
…
,
ar
e
p
r
ed
eter
m
in
ed
l
o
ca
tio
n
s
with
r
esp
ec
t
to
th
e
d
esire
d
p
er
f
o
r
m
an
ce
of
th
e
ASS
[
1
7
,
18
]
.
So
,
th
e
(
9
)
n
ee
d
s
to
be
s
o
lv
ed
.
(
−
(
(
)
)
−
̃
(
(
)
)
)
=
(
−
1
)
(
−
2
)
…
(
−
1
)
(
11
)
No
te
th
at
th
e
m
atr
i
x
(
(
)
)
is
d
ep
en
d
ed
on
th
e
v
el
o
city
of
th
e
ca
r
(
)
.
On
e
of
t
h
e
m
eth
o
d
s
to
s
o
lv
e
(
9
)
is
th
e
m
o
d
al
m
eth
o
d
in
th
e
m
at
er
ial
[
1
9
]
.
T
h
is
m
eth
o
d
u
s
es
th
e
r
eg
r
ess
io
n
ca
lc
u
latio
n
p
r
o
c
ess
.
If
is
r
an
k
of
m
atr
ix
̃
an
d
1
,
2
,
…
,
ar
e
eig
en
v
alu
es
of
m
atr
ix
th
en
th
e
r
eg
r
ess
io
n
ca
lcu
latio
n
p
r
o
ce
s
s
is
im
p
lem
en
te
d
by
n
/m
s
tep
s
,
on
each
s
tep
th
e
m
atr
ix
is
ca
lcu
lated
to
m
o
v
e
m
p
o
les
of
A
a
m
o
n
g
1
,
2
,
…
,
to
n
ew
p
o
les
am
o
n
g
1
,
2
,
…
,
of
m
atr
ix
(
(
)
)
−
̃
(
(
)
)
.
T
h
e
m
atr
ix
(
(
)
)
th
en
is
ca
lcu
lated
by
s
u
m
m
in
g
m
atr
ices
(
(
)
)
.
2
.
2
.
2
.
Desig
nin
g
t
he
o
ute
r
a
da
ptiv
e
co
ntr
o
l
lo
o
p
B
ac
k
to
th
e
ASS
in
p
r
esen
ce
of
n
o
is
e
(
)
ca
u
s
ed
by
r
o
a
d
p
r
o
f
il
e
an
d
v
elo
city
of
th
e
car
(
6
)
,
with
th
e
in
n
er
c
o
n
tr
o
l
l
o
o
p
t
h
e
ASS
m
o
d
el
b
ec
o
m
es
=
̃
(
(
)
)
+
̃
[
(
)
+
(
)
]
(
12
)
in
wh
ich
̃
is
a
s
tab
le
m
atr
ix
h
av
in
g
d
esire
d
p
o
les
1
,
2
,
…
,
.
We
h
av
e
th
e
L
y
ap
u
n
o
v
(
1
1
)
̃
(
(
)
)
+
̃
(
(
)
)
=
−
(
13
)
If
s
y
m
m
etr
ic
m
atr
i
x
Q
is
p
o
s
itiv
e
d
ef
in
ite,
(
1
1
)
alwa
y
s
ex
is
ts
a
u
n
iq
u
e
p
o
s
itiv
e
d
ef
in
ite
s
y
m
m
etr
ic
m
atr
ix
(
(
)
)
[
2
0
]
.
We
u
s
e
th
e
r
ef
er
en
ce
m
o
d
el
d
escr
ib
ed
by
(
1
2
)
:
=
̃
(
(
)
)
+
̃
(
)
(
14
)
Desig
n
in
g
th
e
o
u
ter
ad
ap
tiv
e
co
n
tr
o
l
lo
o
p
is
to
g
u
a
r
an
te
e
th
e
s
y
s
tem
(
1
0
)
tr
ac
k
in
g
to
th
e
s
y
s
tem
(
1
2
)
.
Su
p
p
o
s
e
(
)
=
(
)
,
we
h
av
e
=
̃
(
(
)
)
+
̃
(
(
)
+
(
)
)
(
15
)
So
th
e
task
of
n
o
is
e
atten
u
atio
n
a
d
ap
tiv
e
m
ec
h
an
is
m
is
to
ad
ju
s
t
(
)
in
o
r
d
e
r
to
m
ak
e
th
e
er
r
o
r
(
)
=
(
)
−
(
)
ten
d
to
ze
r
o
,
in
wh
ich
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4
8
5
6
I
nt
J
R
ob
&
A
u
to
m
,
Vo
l.
9
,
N
o
.
4
,
Dec
em
b
er
2
0
2
0
:
2
7
1
–
280
276
=
̃
(
(
)
)
+
̃
(
)
(
16
)
T
h
e
d
iag
r
a
m
of
two
co
n
tr
o
l
lo
o
p
s
f
o
r
ASS
is
s
h
o
wn
in
th
e
Fi
g
u
r
e
5
.
Use
th
e
p
o
s
itiv
e
-
d
ef
in
ite
L
y
a
p
u
n
o
v
c
an
d
id
ate
f
u
n
ctio
n
as
f
o
l
lo
w
s:
(
,
)
=
+
−
(
17
)
in
wh
ich
m
atr
ix
P
is
r
o
o
t
of
L
y
ap
u
n
o
v
f
u
n
ctio
n
(
1
5
)
an
d
H
is
th
e
p
o
s
itiv
e
-
d
ef
in
ite
s
y
m
m
e
tr
ic
m
atr
ix
ch
o
s
en
ar
b
itra
r
ily
.
So
to
k
ee
p
(
,
)
<
0
or
→
f
o
r
all
≠
,
th
e
v
ec
to
r
n
ee
d
s
to
be
s
atis
f
y
(
1
6
)
[
̃
+
−
]
=
(
18
)
T
h
er
ef
o
r
e,
th
e
n
o
is
e
at
ten
u
atio
n
ad
ap
tiv
e
m
ec
h
an
is
m
is
=
−
̃
(
(
)
)
(
19
)
So
m
e
r
em
ar
k
s
:
-
Fu
n
ctio
n
(
,
)
<
0
is
n
eg
ativ
e
-
d
ef
in
ite
with
r
esp
ec
t
to
th
er
ef
o
r
e,
≠
.
In
an
o
th
er
wo
r
d
,
th
e
ad
ap
tiv
e
m
ec
h
an
is
m
(
1
9
)
is
th
e
n
o
is
e
atten
u
atio
n
m
ec
h
an
is
m
,
it
is
not
an
id
en
tific
atio
n
f
u
n
ctio
n
of
n
o
is
e
ca
u
s
ed
by
r
o
ad
p
r
o
f
ile
an
d
v
elo
city
of
t
h
e
ca
r
.
-
T
h
e
v
elo
city
of
ten
d
in
g
to
ze
r
o
of
er
r
o
r
is
d
ep
en
d
e
d
on
th
e
p
o
s
itiv
e
–
d
ef
in
ite
m
atr
ix
Q
.
-
L
ar
g
er
t
h
e
n
o
r
m
of
m
atr
ix
H
is
th
e
f
aster
er
r
o
r
ten
d
to
ze
r
o
d
o
es.
L
ar
g
er
eig
en
v
alu
es
of
m
a
tr
ix
H
a
r
e
th
e
lar
g
er
am
p
litu
d
e
of
is
,
th
is
ca
u
s
es
th
e
o
s
cillatio
n
in
th
e
s
y
s
tem
Fig
u
r
e
5.
T
h
e
d
iag
r
am
of
two
co
n
tr
o
l
lo
o
p
s
f
o
r
ASS:
in
n
er
co
n
tr
o
l
lo
o
p
(
b
lu
e
lin
e)
,
o
u
ter
ad
a
p
tiv
e
co
n
t
r
o
l
lo
o
p
(
r
e
d
lin
e)
2
.
2
.
3
.
T
he
s
im
ula
t
io
n
re
s
u
lt
s
us
ing
t
he
pra
ct
ica
l
ro
a
d
pro
f
ile
da
t
a
T
h
e
s
im
u
latio
n
r
esu
lts
b
elo
w
ar
e
co
n
d
u
cted
in
two
ca
s
es
th
at
ar
e
ev
en
r
o
ad
p
r
o
f
ile
an
d
s
to
ch
asti
c
p
r
ac
tice
r
o
ad
p
r
o
f
ile.
T
h
e
p
h
y
s
ical
p
ar
am
eter
s
of
ASS
ar
e
:
=
0
.
2
,
=
8399
(
)
,
=
151176
(
)
,
=
6665
(
)
,
=
500
(
)
,
=
194
.
2
(
)
,
=
49
(
)
a.
T
h
e
s
im
u
latio
n
r
esu
lts
f
o
r
e
v
e
n
r
o
ad
p
r
o
f
ile
T
h
e
in
itial
co
n
d
itio
n
of
s
tates
is
[
0
;0
.
2
;0
;
0
.
2
]
,
th
e
a
m
p
litu
d
e
of
th
e
ev
en
t
r
o
a
d
p
r
o
f
ile
is
0
.
0
2
m
as
d
escr
ib
ed
in
Fig
u
r
e
6.
T
h
e
v
ar
y
in
g
of
p
o
s
itio
n
,
th
e
v
elo
ci
ty
of
th
e
s
p
r
u
n
g
m
ass
an
d
u
n
s
p
r
u
n
g
m
ass
ar
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
R
ob
&
A
u
to
m
I
SS
N:
2089
-
4
8
5
6
Th
e
a
lg
o
r
ith
m
of
a
d
a
p
tive
co
n
tr
o
l
fo
r
a
ctive
s
u
s
p
en
s
io
n
s
yst
ems
u
s
in
g
p
o
le
a
s
s
ig
n
...
(
C
h
i
N
g
u
ye
n
V
a
n
)
277
d
ep
icted
in
th
e
Fig
u
r
e
7.
In
th
is
f
ig
u
r
e,
th
e
p
ass
iv
e
ca
s
e,
th
e
p
o
le
ass
ig
n
ca
s
e,
an
d
th
e
ad
ap
tiv
e
ca
s
e
ar
e
co
m
p
ar
ed
with
.
In
th
e
ca
s
e
of
p
o
le
ass
ig
n
,
th
e
n
u
m
b
er
of
o
s
cillatio
n
s
of
p
o
s
itio
n
an
d
v
elo
city
of
s
p
r
u
n
g
m
ass
an
d
u
n
s
p
r
u
n
g
m
ass
is
d
ec
r
ea
s
ed
but
th
e
a
m
p
litu
d
e
of
o
s
ci
llatio
n
is
in
cr
ea
s
ed
in
c
o
m
p
ar
is
o
n
to
t
h
e
p
ass
iv
e
ca
s
e.
In
th
e
ca
s
e
of
ad
ap
tiv
e
a
ctiv
e
co
n
tr
o
l,
t
h
e
am
p
litu
d
e
an
d
n
u
m
b
er
of
o
s
cillatio
n
s
ar
e
b
o
th
d
ec
r
ea
s
ed
.
Fig
u
r
e
6.
E
v
en
t
r
o
ad
p
r
o
f
ile
Fig
u
r
e
7.
R
esp
o
n
s
e
of
p
o
s
itio
n
,
v
elo
city
of
th
e
s
p
r
u
n
g
m
ass
an
d
u
n
s
p
r
u
n
g
m
ass
in
th
e
ca
s
e
of
e
v
en
t
r
o
a
d
p
r
o
f
il
e
b.
T
h
e
s
im
u
latio
n
r
esu
lts
f
o
r
s
to
c
h
asti
c
p
r
ac
tice
r
o
ad
p
r
o
f
ile
Pro
b
ab
ilit
y
d
en
s
ity
f
u
n
ctio
n
of
th
e
s
to
c
h
asti
c
p
r
ac
tice
r
o
ad
p
r
o
f
ile
(
as
in
Fig
u
r
e
8)
is
:
=
−
2
.
319
,
=
2
.
348
,
=
0
.
0131
,
=
0
.
0131
;
=
0
.
331678
,
=
0
.
0131
.
T
h
e
s
im
u
latio
n
r
esu
lts
ar
e
co
n
d
u
cted
f
o
r
th
r
ee
v
elo
ci
ties
of
th
e
car
5
k
m
/h
,
40
k
m
/h
an
d
80
k
m
/h
.
Fig
u
r
e
s
9
an
d
10
a
r
e
d
ep
icte
d
th
e
s
im
u
latio
n
o
s
cillatio
n
r
esp
o
n
s
es
of
ASS,
t
h
e
d
y
n
am
ic
w
h
ee
l
lo
ad
an
d
ac
tiv
e
f
o
r
ce
,
r
esp
ec
tiv
ely
.
In
th
ese
f
ig
u
r
es,
th
e
ac
ti
v
e
co
n
tr
o
l
r
esp
o
n
s
es
ar
e
co
m
p
ar
ed
to
th
e
p
ass
iv
e
ca
s
e.
Similar
ly
,
Fig
u
r
e
s
11
an
d
12
s
h
o
w
th
e
s
im
u
latio
n
r
esu
lts
in
th
e
ca
se
th
at
th
e
v
elo
city
of
th
e
car
is
40
k
m
/
h
,
Fig
u
r
e
s
13
an
d
14
p
l
o
t
th
e
r
esu
lts
f
o
r
80
k
m
/h
.
At
5
k
m
/h
of
th
e
v
elo
city
of
th
e
ca
r
,
we
s
ee
th
at
th
e
o
s
cillatio
n
an
d
am
p
litu
d
e
of
o
s
cillatio
n
th
e
s
p
r
u
n
g
m
ass
is
ef
f
ec
tiv
ely
d
ec
r
ea
s
ed
as
s
h
o
wn
in
t
h
e
Fig
u
r
e
9.
T
h
e
ac
tiv
e
c
o
n
tr
o
l
f
o
r
ce
ac
ts
to
th
e
s
y
s
tem
clea
r
ly
at
0
.
5
s
f
r
o
m
th
e
b
eg
i
n
n
in
g
.
E
f
f
icien
c
y
of
th
e
o
s
c
illatio
n
d
ec
r
ea
s
e
of
th
e
ca
r
is
b
e
tter
th
an
t
h
e
wh
ee
l
.
R
ed
u
cin
g
car
o
s
cillatio
n
is
more
ef
f
icien
t
t
h
an
r
e
d
u
cin
g
th
e
wh
ee
l
o
s
cillatio
n
.
T
h
e
d
y
n
a
m
ic
lo
ad
v
a
r
ies
in
r
an
g
e
±
3
0
0
N
,
th
e
ac
tiv
e
c
o
n
tr
o
l
f
o
r
ce
r
an
g
es
f
r
o
m
-
600
N
to
400
N
.
Fig
u
r
e
8.
Sto
ch
asti
c
p
r
ac
tice
r
o
ad
p
r
o
f
ile
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4
8
5
6
I
nt
J
R
ob
&
A
u
to
m
,
Vo
l.
9
,
N
o
.
4
,
Dec
em
b
er
2
0
2
0
:
2
7
1
–
280
278
Fig
u
r
e
9
.
Po
s
itio
n
an
d
v
elo
city
of
s
p
r
u
n
g
m
ass
an
d
u
n
s
p
r
u
n
g
m
ass
f
o
r
ca
s
es:
p
ass
iv
e
an
d
ad
ap
tiv
e
co
n
tr
o
l
at
5
k
m
/h
(
v
e
lo
city
of
th
e
ca
r
)
Fig
u
r
e
10
.
T
h
e
d
y
n
am
ic
w
h
ee
l
lo
ad
an
d
ad
ap
tiv
e
co
n
tr
o
l
f
o
r
ce
at
5
k
m
/h
(
v
elo
ci
ty
of
th
e
ca
r
)
Fig
u
r
e
11.
Po
s
itio
n
an
d
v
elo
ci
ty
of
s
p
r
u
n
g
m
ass
an
d
u
n
s
p
r
u
n
g
m
ass
f
o
r
ca
s
es:
p
ass
iv
e
an
d
ad
ap
tiv
e
co
n
tr
o
l
at
40
k
m
/
h
(
v
elo
city
of
th
e
ca
r
)
Fig
u
r
e
12.
T
h
e
d
y
n
am
ic
w
h
ee
l
lo
ad
an
d
ad
ap
tiv
e
co
n
tr
o
l
f
o
r
ce
at
40
k
m
/
h
(
v
el
o
city
of
th
e
ca
r
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
R
ob
&
A
u
to
m
I
SS
N:
2089
-
4
8
5
6
Th
e
a
lg
o
r
ith
m
of
a
d
a
p
tive
co
n
tr
o
l
fo
r
a
ctive
s
u
s
p
en
s
io
n
s
yst
ems
u
s
in
g
p
o
le
a
s
s
ig
n
...
(
C
h
i
N
g
u
ye
n
V
a
n
)
279
Fig
u
r
e
13
.
Po
s
itio
n
an
d
v
elo
ci
ty
of
s
p
r
u
n
g
m
ass
an
d
u
n
s
p
r
u
n
g
m
ass
f
o
r
ca
s
es:
p
ass
iv
e
an
d
ad
ap
tiv
e
co
n
tr
o
l
at
80
k
m
/
h
(
v
elo
city
of
th
e
ca
r
)
Fig
u
r
e
14
.
T
h
e
d
y
n
am
ic
w
h
ee
l
lo
ad
an
d
ad
ap
tiv
e
co
n
tr
o
l
f
o
r
ce
at
80
k
m
/
h
(
v
el
o
city
of
th
e
ca
r
)
At
car
s
p
ee
d
of
40
k
m
/h
with
ac
tiv
e
ad
ap
tiv
e
co
n
tr
o
l,
th
e
car
o
s
cillatio
n
d
ec
r
ea
s
e
is
q
u
ite
g
o
o
d
in
co
m
p
ar
is
o
n
to
th
e
p
ass
iv
e
ca
s
e.
Fo
r
th
e
f
ir
s
t
0
.
5
s
ec
o
n
d
s
of
th
e
ad
ap
tiv
e
co
n
tr
o
l
p
r
o
ce
s
s
,
th
e
d
y
n
am
ic
wh
ee
l
lo
ad
v
ar
ies
in
t
h
e
r
a
n
g
e
-
3
0
0
N
to
2
0
0
N
,
an
d
af
ter
th
at
th
e
d
y
n
am
ic
w
h
ee
l
lo
ad
d
ec
r
ea
s
es,
it
r
an
g
es
in
±
100
N
.
T
h
e
ac
tiv
e
co
n
tr
o
l
f
o
r
ce
v
ar
ies
f
r
o
m
4
0
0
N
to
400
N
f
o
r
th
e
f
ir
s
t
0
.
5
s
ec
o
n
d
s
an
d
i
t
v
ar
ies
in
th
e
r
an
g
e
±
2
0
0
N
f
o
r
af
ter
t
h
at.
At
car
s
p
ee
d
of
80
k
m
/h
,
th
e
s
im
u
latio
n
r
esu
lts
ar
e
th
e
s
am
e
at
40
k
m
/h
.
T
h
er
ef
o
r
e,
by
u
s
in
g
th
e
ca
s
ca
d
e
ad
ap
tiv
e
c
o
n
tr
o
l
f
o
r
t
h
e
A
SS
,
th
e
o
s
cillatio
n
s
of
th
e
car
an
d
th
e
wh
ee
l
a
r
e
d
ec
r
ea
s
e
d
ef
f
ec
tiv
ely
,
it
is
th
e
s
am
e
ca
s
e
with
th
e
d
y
n
am
ic
lo
ad
.
3.
CO
NCLU
SI
O
N
T
h
e
p
ap
er
in
tr
o
d
u
ce
s
th
e
ca
s
ca
d
e
ad
ap
tiv
e
co
n
tr
o
l
m
eth
o
d
f
o
r
an
ASS
.
T
h
e
in
n
er
co
n
tr
o
l
lo
o
p
u
s
es
th
e
p
o
le
p
lace
m
en
t
tech
n
i
q
u
e
wh
ich
is
u
s
ed
to
p
lace
th
e
clo
s
ed
lo
o
p
p
o
les
of
th
e
s
y
s
tem
with
o
u
t
n
o
is
e
in
p
r
ed
eter
m
in
e
d
lo
ca
tio
n
s
in
o
r
d
er
to
ch
an
g
e
th
e
d
y
n
am
ic
ch
ar
ac
ter
is
tics
of
A
SS
to
d
esire
d
p
er
f
o
r
m
a
n
ce
r
eq
u
ir
em
e
n
ts
.
T
h
e
o
u
ter
co
n
t
r
o
l
lo
o
p
u
s
es
th
e
ad
ap
tiv
e
c
o
n
tr
o
l
s
tr
ateg
y
with
th
e
a
d
ap
tiv
e
m
ec
h
an
is
m
to
co
m
p
en
s
ate
f
o
r
th
e
o
s
cillatio
n
of
th
e
car
ca
u
s
ed
by
th
e
r
o
ad
p
r
o
f
ile
a
n
d
v
el
o
city
of
th
e
ca
r
ac
tin
g
to
ASS.
T
h
e
s
im
u
latio
n
r
esu
lts
u
s
in
g
ev
en
r
o
a
d
p
r
o
f
ile
an
d
s
to
ch
asti
c
p
r
ac
tice
r
o
ad
p
r
o
f
ile
s
h
o
w
th
at
th
e
ca
p
ab
ilit
y
of
o
s
cillatio
n
d
ec
r
ea
s
e
f
o
r
th
e
ca
r
an
d
th
e
wh
ee
l
of
ASS
is
q
u
ite
ef
f
icien
t.
T
h
e
d
y
n
am
ic
wh
ee
l
lo
ad
is
d
ec
r
ea
s
ed
so
th
e
r
id
e
co
m
f
o
r
t
of
p
ass
en
g
er
s
is
b
etter
.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
is
r
esear
ch
is
s
u
p
p
o
r
ted
f
in
a
n
cially
by
T
h
ai
Ng
u
y
e
n
Un
iv
e
r
s
ity
of
T
ec
h
n
o
lo
g
y
,
T
NUT
.
RE
F
E
R
E
NC
E
S
[1
]
D.
Ka
rn
o
p
p
,
“
Th
e
o
re
t
ica
l
Li
m
it
a
ti
o
n
s
in
Ac
ti
v
e
Ve
h
icle
S
u
s
p
e
n
si
o
n
s,
”
Ve
h
icle
S
y
ste
m
Dy
n
a
mic
s
,
v
o
l.
1
5
,
n
o
.
1,
pp.
41
-
5
4
,
1
9
8
6
.
[2
]
M.
C.
S
m
it
h
,
“
Ac
h
iev
a
b
le
Dy
n
a
m
ic
Re
sp
o
n
se
fo
r
Au
to
m
o
ti
v
e
Ac
ti
v
e
S
u
sp
e
n
si
o
n
s,
”
Veh
icle
S
y
ste
m
Dy
n
a
mic
s
,
v
o
l.
2
4
,
no.
1,
p
p
.
1
-
33
,
1
9
9
5
.
[3
]
J.
Lin
a
n
d
R.
L
ian
,
“
I
n
telli
g
e
n
t
Co
n
tro
l
of
Ac
ti
v
e
S
u
sp
e
n
si
o
n
S
y
ste
m
s,
”
IEE
E
T
r
a
n
sa
c
ti
o
n
s
on
In
d
u
stri
a
l
El
e
c
tro
n
ics
,
v
o
l.
5
8
,
no.
2,
p
p
.
6
1
8
-
6
2
8
,
2
0
1
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4
8
5
6
I
nt
J
R
ob
&
A
u
to
m
,
Vo
l.
9
,
N
o
.
4
,
Dec
em
b
er
2
0
2
0
:
2
7
1
–
280
280
[4
]
A.
Tu
r
n
i
p
,
et
al
.
,
“
Co
n
tr
o
ll
e
r
d
e
sig
n
fo
r
a
c
ti
v
e
s
u
sp
e
n
si
o
n
sy
ste
m
b
a
se
d
on
sk
y
h
o
o
k
re
fe
re
n
c
e
m
o
d
e
l,
”
in
2
0
1
5
In
ter
n
a
t
io
n
a
l
Co
n
fer
e
n
c
e
on
T
e
c
h
n
o
lo
g
y
,
I
n
fo
rm
a
ti
c
s,
M
a
n
a
g
e
me
n
t,
En
g
in
e
e
rin
g
&
En
v
iro
n
me
n
t
(
T
IM
E
-
E)
,
2
0
1
5
,
pp.
1
4
7
-
1
5
1
.
[5
]
V.
S.
De
sh
p
a
n
d
e
,
M.
B
h
a
sk
a
ra
,
a
n
d
S.
B.
P
h
a
d
k
e
,
“
S
li
d
in
g
m
o
d
e
c
o
n
tro
l
of
a
c
ti
v
e
su
s
p
e
n
sio
n
sy
ste
m
s
u
si
n
g
a
d
istu
r
b
a
n
c
e
o
b
se
r
v
e
r,
”
in
2
0
1
2
1
2
t
h
In
ter
n
a
ti
o
n
a
l
W
o
rk
sh
o
p
on
Va
ria
b
le
S
tr
u
c
tu
re
S
y
ste
ms
,
2
0
1
2
,
pp.
70
-
7
5
.
[6
]
W.
Ju
e
a
n
d
Z.
Jin
g
,
“
M
o
d
e
l
-
fre
e
trac
k
in
g
c
o
n
tr
o
l
fo
r
v
e
h
icle
a
c
ti
v
e
su
sp
e
n
sio
n
sy
ste
m
s,
”
in
2
0
1
5
3
4
t
h
Ch
i
n
e
se
Co
n
tro
l
Co
n
fer
e
n
c
e
(CCC)
,
2
0
1
5
,
pp.
8
0
6
7
-
8
0
7
2
.
[7
]
F.
Bra
g
h
i
n
,
F.
Re
sta
,
a
n
d
E.
S
a
b
b
i
o
n
i
,
“
A
m
o
d
a
l
c
o
n
tr
o
l
fo
r
a
c
ti
v
e
/se
m
i
-
a
c
ti
v
e
su
sp
e
n
sio
n
sy
st
e
m
s,
”
in
2
0
0
7
IEE
E/
AS
M
E
in
ter
n
a
ti
o
n
a
l
c
o
n
fer
e
n
c
e
on
a
d
v
a
n
c
e
d
i
n
telli
g
e
n
t
me
c
h
a
tro
n
ics
,
2
0
0
7
,
p
p
.
1
-
6.
[8
]
B.
Z
h
a
n
g
,
M.
F
a
n
,
a
n
d
F.
M
iao
,
“
Op
ti
m
a
l
Co
n
tro
l
of
Ve
h
icle
Ac
ti
v
e
S
u
sp
e
n
si
o
n
S
y
ste
m
s
with
Ac
t
u
a
to
r
De
lay
,
”
in
2
0
0
7
IE
EE
I
n
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
on
C
o
n
tro
l
a
n
d
A
u
to
m
a
ti
o
n
,
2
0
0
7
,
p
p
.
2
2
5
7
-
2
2
6
1
.
[9
]
A.
Alley
n
e
a
n
d
J.
K.
He
d
rick
,
“
N
o
n
li
n
e
a
r
Co
n
tr
o
l
of
a
Qu
a
rter
Ca
r
Ac
ti
v
e
S
u
s
p
e
n
sio
n
,
”
in
1
9
9
2
Ame
ric
a
n
C
o
n
tr
o
l
Co
n
fer
e
n
c
e
,
1
9
9
2
,
pp.
21
-
2
5
.
[1
0
]
G.
Tan
g
,
H.
Li
n
,
a
n
d
H.
S
u
,
“
De
c
o
u
p
l
in
g
v
ib
ra
t
io
n
c
o
n
tr
o
l
fo
r
a
c
t
iv
e
su
sp
e
n
sio
n
sy
ste
m
s,
”
in
2
0
1
7
2
9
th
C
h
in
e
se
Co
n
tro
l
a
n
d
De
c
isio
n
C
o
n
fer
e
n
c
e
(CCDC)
,
2
0
1
7
,
pp.
6
5
0
4
-
6
5
0
9
.
[1
1
]
K.
Ba
n
sa
l
a
n
d
P.
M
u
k
h
ij
a
,
“
Ev
e
n
t
-
tri
g
g
e
re
d
c
o
n
tr
o
l
of
v
e
h
icle
a
c
ti
v
e
su
s
p
e
n
sio
n
s
y
ste
m
s,
”
in
2
0
1
8
In
d
i
a
n
Co
n
tro
l
Co
n
fer
e
n
c
e
(ICC)
,
2
0
1
8
,
p
p
.
1
7
8
-
1
8
3
.
[1
2
]
S.
-
j.
Li
u
,
Z.
-
h.
Hu
a
n
g
,
a
n
d
Y.
-
z.
Ch
e
n
,
“
Au
t
o
m
o
b
il
e
a
c
ti
v
e
su
s
p
e
n
sio
n
sy
ste
m
wit
h
fu
z
z
y
c
o
n
tr
o
l,
”
J
o
u
rn
a
l
of
Ce
n
tra
l
S
o
u
th
U
n
ive
rs
it
y
of
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
11,
n
o
.
2,
p
p
.
2
0
6
-
2
0
9
,
2
0
0
4
.
[1
3
]
C
.
N
.
Va
n
,
“
S
tate
Esti
m
a
ti
o
n
Ba
se
d
on
S
i
g
m
a
P
o
i
n
t
Ka
lma
n
F
il
t
e
r
fo
r
S
u
sp
e
n
si
o
n
S
y
ste
m
in
P
re
se
n
c
e
of
Ro
a
d
Ex
c
it
a
ti
o
n
I
n
flu
e
n
c
e
d
by
Ve
lo
c
it
y
of
t
h
e
Ca
r
,
”
J
o
u
r
n
a
l
of
C
o
n
tr
o
l
S
c
ien
c
e
and
En
g
in
e
e
rin
g
,
v
o
l
.
2
0
1
9
,
2
0
1
9
.
[1
4
]
G.
Ko
c
h
a
n
d
T.
Kl
o
ib
e
r,
“
Driv
i
n
g
S
tate
Ad
a
p
t
iv
e
C
o
n
tr
o
l
of
an
Ac
ti
v
e
Ve
h
icle
S
u
sp
e
n
si
o
n
S
y
s
tem
,
”
in
IEE
E
T
ra
n
sa
c
ti
o
n
s
on
Co
n
tro
l
S
y
ste
ms
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
22,
n
o
.
1,
pp.
44
-
57
,
2
0
1
4
.
[1
5
]
D.
Hro
v
a
t,
“
S
u
r
v
e
y
of
a
d
v
a
n
c
e
d
su
sp
e
n
sio
n
d
e
v
e
l
o
p
m
e
n
ts
a
n
d
re
late
d
o
p
ti
m
a
l
c
o
n
tr
o
l
a
p
p
li
c
a
ti
o
n
s,
”
Au
to
ma
ti
c
a
,
v
o
l.
3
3
,
no.
1
0
,
pp.
1
7
8
1
-
1
8
1
7
,
1
9
9
7
.
[1
6
]
G.
Ko
c
h
,
et
al
.
,
“
A
n
o
n
li
n
e
a
r
e
stim
a
to
r
c
o
n
c
e
p
t
f
o
r
a
c
ti
v
e
v
e
h
icle
su
sp
e
n
sio
n
c
o
n
tro
l,
”
in
Pro
c
e
e
d
i
n
g
s
of
t
h
e
2
0
1
0
Ame
ric
a
n
Co
n
tro
l
C
o
n
fer
e
n
c
e
,
2
0
1
0
,
p
p
.
4
5
7
6
-
4
5
8
1
.
[1
7
]
K.
Og
a
ta,
M
o
d
e
rn
Co
n
tro
l
En
g
in
e
e
rin
g
.
P
re
n
ti
c
e
Ha
ll
P
TR,
2
0
0
1
.
[1
8
]
C.
N.
Va
n
a
n
d
P.
N.
Do
a
n
,
“
Ad
a
p
ti
v
e
trac
k
i
n
g
c
o
n
tr
o
l
b
a
se
d
on
d
istu
r
b
a
n
c
e
a
tt
e
n
u
a
ti
o
n
a
n
d
IS
S
sta
b
il
iza
ti
o
n
of
Eu
ler
-
Lag
ra
n
g
e
n
o
n
li
n
e
a
r
sy
ste
m
s
in
th
e
p
re
se
n
c
e
of
u
n
c
e
rtain
ty
a
n
d
i
n
p
u
t
n
o
ise
,
”
in
2
0
1
1
2
n
d
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
on
Arti
fi
c
ia
l
I
n
telli
g
e
n
c
e
,
M
a
n
a
g
e
me
n
t
S
c
ien
c
e
a
n
d
El
e
c
tro
n
ic
Co
mm
e
rc
e
(AI
M
S
EC)
,
2
0
1
1
,
p
p
.
3
6
9
8
-
3
7
0
1
.
[1
9
]
G.
Ya
o
,
et
al
.
,
“
M
o
d
a
l
c
o
m
p
u
ti
n
g
m
e
th
o
d
of
o
u
tp
u
t
fe
e
d
b
a
c
k
c
o
n
tro
l
g
a
i
n
m
a
tri
x
in
p
o
le
a
ss
ig
n
m
e
n
t
of
v
i
b
ra
ti
o
n
sy
ste
m
,
”
in
2
0
1
0
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
on
M
e
c
h
a
n
ic
Au
to
m
a
ti
o
n
a
n
d
Co
n
tro
l
E
n
g
i
n
e
e
rin
g
,
2
0
1
0
,
p
p
.
2
2
4
3
-
2
2
4
7
.
[2
0
]
G.
Kitag
a
wa
,
“
An
a
lg
o
rit
h
m
fo
r
s
o
lv
i
n
g
t
h
e
m
a
tri
x
e
q
u
a
ti
o
n
X
=
F
XF
T
+
S,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
of
Co
n
tro
l
,
v
o
l
.
25,
n
o
.
5,
p
p
.
7
4
5
-
7
5
3
,
1
9
7
7
.
Evaluation Warning : The document was created with Spire.PDF for Python.