二階徵分方程式的解法及其估計
THE METHODS AND ERROR ESTlMATIONS ON THE SECOND-ORDER
DIFFERENTIAL EQUAT工ONS. w a
--hu • L SC -a v-nr bet Rs b qA n a y工 n this paper
,
we solve the 工 nitial Value Problem (IVP)by a Modified Predictor-Corrector method. We can prove i t
has trucncation error Q(h4 ) and i t is stable. For Boundary
Value Problems (BVP)
,
Shooting method and Finite-Differencemethod are often used. We improve these methods and get some theorems and error estimations.
師大學報第卅二期
THE METHODS AND ERROk .t; ST 工 MAT 工 ONS ON THE
SECOND-ORDER D 工 FFERENTIAL EQUAT 工 ONS
REN-SHIAW YANG
DEPARTMENT OF MATHEMAT 工 CS
TAIWAN NORMAL UN 工 VERSITY
TA 工 PE 工, TA 工 WAN , R. O. C.
工 NTRODUCTION
工 n this paper
,
we will discuss two types of the secondorder differential eguations of the following form:
(工 y" = f(x,y,y') , a < x < b and (P) y(a) = c y' (a) =.d _y" + f(y) =0 y (a) =c y (b) =d
,
a < x< bOn the f i r s t type 工), there' are many packages
developed such as PHASER which involves Euler's Method [7]
,
工 mproved Euler's Method [5] and Runge-Kutta Method [6]. But
for more accurate
,
we use multistep methods and thenpredic-tor-corrector techniques is can also be developed. For
controlling the error
,
the main purpose is each componentmust be accurate. So wedevelop a modified method (combine
Runge-Kutta Method
,
Adams~Bashforth Method [5] andAdams-Moulton Method [5]) and take.a small number r (seè step 2 .òf
the following algorithm) to solve this system (主) •
On the second type (P)
,
Shooting Method and DifferenceMethod are often used. But for stability
,
we use二階徵分方程式的解法及其估計
step 2: (Compute starting values using Runge-Kutta method.) Forward by a (very small) distance r
,
and tocalculate
Kn r
*
f(a, ya) ya.
==y(a) ==c Ylâ.==
Ya+ ka k1d == r*
f(a+r, Y,
a
可 == Ya.+
k 1a ]<;1 r.*
f(a+ 玄,有 Y 2&.
== Y + 2klkz
ð.. == r*
f ( a + 2 r , Y 2d. ) Y2 Yq
+ (ka+ 2klâ.
+ 2k 1 + k2~) /6step 3: (Adams-Bashforth three-step method for predictor and Adams-Moulton three-step method for corrector) ( s e t x = a + i h l 有Q. == Y3 + Y4 == Y3 + h {5f (x1 '叫卜 16f( 勻, Y2 )+23f (勻,Yj)}/12 h{f( 呵,可 )-5f (巧,Y2 ) + 1 9f (勻 'Y;3 ) +9f( 旬, Y咱)}/24 ) ←」 14 u s e r 、 V 』 vt e'-heL tx 一
!
←」 ut- pu- tp- ut-ou 一 (。一..
4. p e +」 S step 5: stopFor example
,
we will solve the followin9 initial value problem: 。 }' 「4. (-←」 r6 )q2 X}s9 -門, LII 「3 Y{-11 f 、←」 Dιda *r*1 .lq3. PS+3 *IJ1= ﹒工可 d ﹒工 。‘一 -Dι -= E'e -一 )or 。 {e H{Eh yyyw /flstJ 、 tltk < x < 2 sqrt(2)==1.4142135...We write a program (using above a 工 gorithm) to solve this prob18m. The program and output are listed in Appendix.
師大學報第卅二期
(1) Predictor-corrector Method for 工 nitial value problems
Suppose we will slove the initial value problem:
(工 VP)
( Y = f ( X Y Y ) y(a) = c
y' (a) =d
a < x 三 b ,
We can set upon a system equations:
( u 1 = y
,
u2 y'
u1 (a) = c
u2 (a) = d
then
,
to solve (TVP) is equivalent to solve the followihg differential equations (Q) of first order:( u l ' = u2
,
u 1( a) =c(Q)
l
u2" = f(x,
u1,
u2),
u2(a) = d/ Since (Q) contains two differential equations of first order and from the predictor-corrector method techrtique for first order
,
we can develöp an algorithm as follows:PRED 工 CTOR-CORRECTOR ALGOR 工 THM:
To approximate the solution of the initial-value problem:
f(x
,
y) a ~ x < b,
cStep 1:(Set initial values)
三階微分方程式的解法及其估計
We know that Adams-Bashforth Three-Step Method has
3
truncation error O(h~) and Adams-Mou 工 ton Three-Step Method
4
has truncation error O(h~) ([5]). We also know that the
predictordashcorrector method has the same order of accuracy 4
as the implicit method
,
that is O(h~) ([13]). Since theRunge-Kutta Method of order four has local truncation error
O(h ), we conclude that this method has lo~al truncation
error O(h)
For Runge-Kutta Method
,
the local truncation errorapproaches to zero as the step size approaches zerOi that
is
,
the method is convergent. Adams-Bashforth Three-StepMethod and Adams-Moulton Three-Step Method satisfy the root
condition
,
so they are also convergent. Therefore,
thedeveloped method is stable.
(2) Finite Difference Method for Boundary Value problem
Consider finite difference methods for the special
class of nonlinear BVP's given by
-u" + f(u) = 0
,
0 三 x < 1 (P) u(O) = cu( 1 ) d
Our primary concern 土 s producxing a tractable numerical
method for this problem. We shall see that
,
under fairlymild aS5umption on f
,
that i t i5 possible to construct andanalyze for (P) which are of high accuracy. Applying the difference approximation
-u(x. -uH{XJ)2 J - 1 + 2u (x , ) - u (x. 2 h J+ 1
第卅三期 師大學報 ~ N-2
,
equations < J system of(72-J(刊=;
2w. -
W:'.,
+h "f (w 布) J-1 臼 J "J+ 1 . U.,..
J -wN- 2 + 2wN_1 + hGf(wN_1)=
d,
1/N is the grid spacing and Vf ~U(x~ ).
, J in matrix form as 2 0
,
-the discrete the ODE yields(P h) to 己 ystem The 『 h 1ilhere g( 見玉, {g( 足) } j f (Wj )
,
k i spositive gefinite
,
and 乏=(c,
0,....,
0,
d ) TThe algebraic system (A) ls nonlinear
,
iteration is necessary to therf concisely written kw + h ♂-1 →RN-1 can be (Ph) (A) and kind symetric some bence g: where 。 W 戶 t approximation 。 ur produce of first decide factor multiplying g
,
to get the iteration we 。f Because step
2
, (i ) =玉- h- g(主) • convergence properties of (工 1 ),
algebra.[2,
at each ‘‘', 1e +h it 's-. 、 w~e bkq-V4 1-a n a k invert simply ) -T 止 { need we To nu 「4 斗 nr 們 G 4Y 戶 IY n a r o f--linear from lemma following the its A. then 11 112 T 久、 min 11 之 I~ 丘之〈JZi mxllz||?
where "}、miniAjiλmax for a11 eig~nvalues令。 f
is symmetric and postive defnite
,
then又 j n*n matrix
,
symmetric a 1. S A A proof: eigenvalues 工 f 工 f Lemma. its and Thus e v --• L -L-sn 。 R p n a Dι s and real and are orthonrmal are V恥『吋
}C.3 啊,「 d f'1-L~' 、=-nz-3
s--aF r切
YN c e v n e qd .工 e'
、正呵, ι Y cl.J
丸maxn
λ. <入 max 主 3 一=♂ d
j =1 J yTl\.y that s 。 j =1 of convergence the lower bound. e p1J 14 司, •• a6 n3 a4.
op ιL 『I qL 4. Dι the n o --令」 -l s' 。 3 P1 [ aflk -nh' -1,
E T4 wt 、 。 n forλand 佇11n similarly iteration are We and the二階微分方程式的解法及其估計
then determined by (1
1)
,
戶 (i)=1: 目 2{i) , HillIE{i}
卅一 r
,,-"'(0)" '
f (5) 1 11 e.' v '1 m11l11ε(1)
112
H '~hcorem : (2 ) < 、15 the sm<llle5t cigenvalue of k.
。 l > mll1 where ) ,4 γaa { and (11.) from have-
,
We Proof: (i) g(之)) • =-112(9{2) ke (1+1)..
』 -h Ie
-。 D ‘ m 。 c 、 J } hi ι .. 』, 1. 、 J -3w eF-A LH ←』 c0l1s1der •• EJ '} LL 、', -n1,
qd-i .,也, E ‘ rw 呵 { eqJ I i 恥、 lerm on t:lle '1'0 ana1yze } ﹒旬, d w {-EL=
'
} .、品 , E 、.、', e .、 J S { FA (g(~) 、 -lhus 2_ (i) = -h~De '、圖, } 可 -A + -l14 r 、 a e~n ko qd a ., .• • G Thus.
) .、 J qH ( -SL 2 , ~(i+l) , T~_(i) -h~(e ,---, )ADe -一 D. . JJ mat:rix with.element:s a lS where 0=
(i+1)1'. (i+l) (e' - --, ) ke ( 3 ) right: } -l f ‘.、 J e ) ,且也 + .、品 { .可 J e } ﹒『 J RM {,
SL 唔,晶,主 白,“= N-3 白 白 t:he (i+1),T ~_(i)I
(皂 }DB term on the at look ^gain,
是 maffh)||lji叫11
2
!I
!t( i)16
we get fllhz d 到 『4,
..
A 斗, .可 A e~ EH FA ( 3),
side of left: 可4 1 1 〈、 t:heIb(i叫I ~
。 n l using Lemma IJence, mé\x A m11l (2) . t:o immediat:ely leads which l < i f converges Ami I1 müxI
f I (s)I
i t:erat:ion '、 h"" = the U t:hen,
Clearly,
師大學報第卅二期
g:
The eigenva1ues of k do depend on N
=
1/h,
and in fact it Cëln be 2shoWI1 tha t.入:~ = O(h'). 'fhus u = 0(1) and so conVergenCe is.itot SQ
m~n
Dutomatic as it seems. We nced to modify (1
1) to improve matters. To improve (1
1) we 100k at thc definition of u
.
We add a COl\st-i1llt to the diago/la1 of a matrix shifts the eigellva1ues: if
A t.
=
"'1.
I• ,-J ,..,..,'
l.I
ic
lI(A + vl)z = ( ,,+ y)z.
'.Iot!vated by this we add:!: v.'己 i l1 to (A) to get
(A ' ) (k+VI )if+(h29{3) - v~)
=
.、,r,
which leads to the i l:eration
E
Ta-{ ( i+ 1) _._ I L 2 _ I • • ( i ) \ .... ( i )
(k + vI) 之=! - (h~g( X!\-')
^"
ana1ysis simi1ar 1:0 thal: used in Theorem 1 shows that,
for_ (i) ;::J ( i )
=
w - w'-' . we nave 9桐、"11 兒(
i ) 11 2 <(u
(v)1
i 11~(
0 ) 112 where u(v)=
) s { ZL 『4 l v xR nuιLW ms v+"
nunobvious1y we want to choose v 50 that u(v) < 1
,
andu(v) is as smalli1S possib1e.
Theorem 2: I f f '(s }iEOfor al l.s , and vZhzmax f '(s ),
v - h2 min f'(s)
then
u (v)
=
<1v ... " m~n för a11 h.
二階微分-方程式的解法及其估計 1、 roof: UIlJcr lhe hypolhcsns of f nnd v
,
max
I
v - .h 2 f ' (口 )|=max(v-i12f'{s)),=
v 呵 h
2min
f'(5),
which i5 strictly le55 than v
.
lJut v +λ>v , hence the rati 。m~n
u(v)< .1.
Since u(v) is a non-decreasillg function for v 主 0 , we wish t 。
take v a5 small as possible to a~lieve minimum convergence factor
u(v). Theorem 2 appears to give. condltions for finding the optimal
v
,
but in fact dοes not. Because Theorem 2 gives only sufficient conditions for u(v) <1,
not neces.ary ones; u(v) <1 is p 。正sible even when the hypotheses of Theoem 2 do' not hold. Generally,
(Ir )wil1
converge so lol\g as f' (s) ~ 0 on a larg.e enough interval containil\g
會 he boundary values.
We are now toexamine theerror in approximating solutions
to (P) using our nonlinear algorithm. The analysis foilows mucll
lhe same lines as the linear casc. If the vector 均=
f
u,( X j)I i s the vector of the exact solution evaluated at x.;' l~ j 乏 N-l , then3
(4 ) KEa
+1129( 山}=r+112z ,
可?戶﹒<:h2
,
where C dr.
pcnds ollly on the c;ierü;atives of u,.
叫 th 11 7. 11正
Subtracting $4) and (A) we get
k(足, -23)+h2{9{E,}-9{1))=
2z~ 2z~ -n --YN D 司正 ku'
+ WM 「 k u~r 、 = Y“
r 。 SL O Swhere D is a diagonal matrix with entries Dj = i4xj)and wyThus
闕 ,甜甜
"
可 -a D 弓,必 』 H + 'bhi 呵, hiE
ZEh--C
=〈\昌 ﹒『 .J W ﹒『 Ed x "可 M 間 ,、、 期似 .o •-mo
卅 第 報。 學 大 師based on the f0110wing 1emma.
Lemma z zf Dj=f'{sj}and E '{s }事。~"> 0
,
for a11 5,
thenII(
I(
k + h k+
h 20 ) -2 0 ) -111,國<
J 1/(h20").Proof: k+ h20 = Q(1 -C)
,
where Q i5 diagonal,
Qj = 2 + h20j,
and each row of C has at most two non-zero entries
,
viz.,
=-l/{2+112D. } , C =-l/(2+lE2D ).
j-l -
-..., \'
,- JI Uj_l" "j+1 -...,
\~..
....j+1月l'hus
~cll...
<2/(2 +h
2,σ)
< 1 .and s 。II(k
+ h20)-l.11..
~
IIQ-
1IL [
1 _~clI...
J
l
r
1 < 、 2 + h-a- I 1- --~-2 + h-(7" l -2 +h
2,σ-
2 自=1/(11;σ}
We have thus estab1ished
,
under the condition f'(s)3 (7" >0,
that
-1.2 !u
,
(x..:) - W.!! .5 C,IT'
-"'hO~ j這 N'
-,'
"j , .. j 、 lwhere C
1 depends onbounds for the third and fourth derivatives of u
.
(i)
since we a1most a1ways are working w1th ~\~I instead of ~
,
we 11.. ..(1)/1have the addi tiona1 error term ,. 11 w - W
\...,
11二階微分方程式的解法及其估計 ( i) I lu(x.!) -w~"'/1 O 吉 j 空 N J J 、
11 旦- ~II...
+
1
~ -兌付) 11 阿
< < 、 cf-lt12+!ls-di}lL,
C
1
小
~1h2
+(u(V))ill~112
' ( 0)assurnir193zo . w e thus are interested in taki 呵 i 1ar.ge enough
so that
i ".. 2
(u(v)}.I.
=
Q(h"'"),
in order to preserve accuracy.
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[1) A1exander
,
R.,
Diagona11y implicit Runge-Kutta method~ f。早stiff O.D.E.'s
,
SIAM J.Numer. Anal.,
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,
k.,
An Introduction to Numerical Analysis. John Wiley, New York ,工 978[)) Boyce
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,
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PWS Doston.,
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J.,
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Math.Comp.,
1',
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,
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,
L.,
and N. Levinson,
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McGraw;-lIi l l,
New York,
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,
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,
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Numerical Methods for Two~Point 80undary Value Problems,
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Numerical Solution of Two-point 80uridary Value Problems,
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,
Numerical Solution of Ordinary Differential Equations,
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,
Computer Solution of Differential二階傲分方程式的解法及其估計
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二階徵分方程式的解法及其估計
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二階微分方程式的解法及其估計
摘要 數學系﹒楊岳孝 本丈中,我們將研究下列二種類別的二階微分方程式之修飾解法: ( 1)r
y" = f ( x , y , y') , a 三三 x 三三 b ~ y (a)=c l y' (a) =d及
.(p)r _y"
+f(y)=O,
a 至 x 三三 b -{ y(a)=c \. y (b)=d 對於第一類型( 1 )的解法,目前有套裝軟體發展,如 P~SER ,其中使用的方法有 Euler's Method , Improved Eùler's Method 及 Runge-Kutta Met-hod 。但為使解更精確,我們探用 Multistep rnethod 旦使用 predictor-
corr-ector 的技巧,通常,我們為了控制錯誤至最小,最主要是要使每一部分的答案
均應準確。因此,我們發展一修飾的解法(融合 Runge-kutta Method, Adams
";" Bashforth Method
,
Adams -Moulton Method )並適當選取一小數 r (見第 一部分文中演算法之步驟 2 )來解此問題。對於第二類型 (P) 的解法通常使用打靶法及有限差分法,但為顧及穩定性, 我們探用有限差分法後再加以改進。然後,我們再討論此解法具較高的精確度。