Internat. J. Math. & Math. Sci.
Vol. 9 No. 4 (1986) 731-732
731
DECOMPOSITION SOLUTION FOR DUFFING AND
VAN DER POL OSCILLATORS
G. ADOMIAN
Center for Applied Mathematics
University of Georgia
Athens, Georgia 30602 U.S.A.
(Received February 13, 1986)
ABSTRACT.
The decomposition method is applied to solve the Duffing and Van der Pol
oscillators without customary restrictive assumptions [I-4] and without resort to
perturbation methods.
1980 AMS MATHEMATICS SUBJECT CLASSIFICATION CODES. 36G20
KEY WORDS AND PHRASES. Duffing oscillator, Van der Pol oscillator, nonlinear,
stochastic, decomposition.
I.
INTRODUCTION
The Duffing equation is written
+
+ By +
yy3
x(t)
(l.l)
The Van der Pol equation can be written
J}
Y +
-,
(If
L
+ BY + y(d/dt)y 3
d2/dt 2,
B
l,
e(d/dt) +
R
y
/3,
B,
Ny
x(t)
(I.2)
we have the form usually given.) Write
in (l.l) and y(d/dt)y 3 in (I.2) Thus
yy3
both are written
Ly + Ry + Ny
x(t)
(1.3)
in the standard form for the decomposition method [I-3] where
definite integral from 0 to t. Then,
Ly
x(t)
Ry- Ny.
Assuming initial conditions
define
by
YO
YO
(l .4)
y(O), y’(O) are specified, let y
y(O) + ty’(O) +
L-Ix(t).
Then
Yn+l
for n>O.
s the two-fol d
-L-l(d/dt)Yn L-I BYn L-I [Ny]
n=OYn
and
732
G. ADOMIAN
2. SOLUTION OF THE PROBLEM
To get computable solutions, we need only substitute for
for the Duffing case and
y(d/dt)
A
y
Z
A
n=O n
for the Van der Pol case where the A are
n
n=O n
Adomian’s polynomials [I-5] generated for the nonlinear term
it exactly in a rapidly converging series
A0
Ny the sum
y3
and representing
[I-5].
yg
3yy
A2 3yY2 + 3YoY
A
+
+
The deterministic problem is now solved.since all components of y are determined.
n-i
which, because of the rapid convergence,
We use an n-term approximation
n (say half a dozen or so terms) but
is generally sufficient with a very
easily carried as far as necessary since the integrals do not involve difficult
Green’s functions. Convergence has been previously established by Adomian [2,5]
and has been shown [2] to be quite rapid.
For the stochastic case [2], none of the usual approximations of statistical
inearization are necessary. The x(t) need not be stationary nor Gaussian nor
delta-correlated. Further e,B,Y and the initial conditions can be stochastic.
No "smallnesS’ assumptions are necessary for the stochastic processes and the nonlinearities. No linearization is used. We can allow
<=> + {, B <B> + n,
{(d/dt)y y
y (R)<y> + o and write Ly x
<=>(d/dt)y <B>y
A and proceed as before with Y
o
n u
result is a stochastic series
which statistics are obtained without
the problems of statistical separability of quantities such as <Ry> where
R d/dt n which normally require closure approximations.
..^Yi
n sVl
Z
n=OTe
Z^ Yn"
<y>noAn
fro
REFERENCES
ADOMIAN, G. Stochastic Systems, Academic Press, 1983.
ADOMIAN, G. Nonlinear Stochastic Operator Equations, Academic Press, 1986.
BELLMAN, R.E., ADOMIAN, G. Nonlinear Partial Differential Equations New
Methods for Their Treatment and Ap_pl’iations, Reidel, 1985.
4. ADOMIAN, G., RACH, R. Anharmonic Oscillator Systems, J. Math. Anal. and Applic.
(January 1983), 229-236.
9__I, no.
5. ADOMIAN, G. Convergent Series Solution of Nonlinear Equations, J. Comput. and
App. Math. ll, no. 2 (October 1984), 225-230.
6. BONZANI, I. On a Class of Nonlinear Stochastic Dynamical Systems" Analysis
of the Transient Behavior, J. Math. Anal. and Applic., to appear.
I.
2.
3.
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