Lecture Notes in Differential Equations - Bruce E. Shapiro

Lecture Notes in Differential Equations - Bruce E. Shapiro Lecture Notes in Differential Equations - Bruce E. Shapiro

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324 LESSON 31. LINEAR SYSTEMS for some set of unknown functions u 1 (t), ..., u n (t), and u = (u 1 (t) u 2 (t) · · · u n (t)) T . Differentiating (31.166) gives y ′ P = (Wu) ′ = W ′ u + Wu ′ (31.167) Substitution into the differential equation (31.164) gives Since W ′ = AW, Subtracting the commong term AWu gives W ′ u + Wu ′ = AWu + g (31.168) AWu + Wu ′ = AWu + g (31.169) Multiplying both sides of the equation by W −1 gives Wu ′ = g (31.170) du dt = u′ = W −1 g (31.171) Since W = e At , W −1 = e −At , and therefore ∫ ∫ du u(t) = dt dt = e −At g(t)dt (31.172) Substition of (31.172) into (31.166) yields the desired result, using the fact that W = e At . Example 31.5. Find a particular solution to the system } x ′ = x + 3y + 5 y ′ = 4x − 3y + 6t The problem can be restated in the form y ′ = Ay + g where ( ) ( ) 1 3 5 A = , and g(t) = 4 −3 6t (31.173) (31.174) We first solve the homogeneous system. The eigenvalues of A satisfy 0 = (1 − λ)(−3 − λ) − 12 (31.175) = λ 2 + 2λ − 15 (31.176) = (λ − 3)(λ + 5) (31.177)

325 so that λ = 3, −5. The eigenvectors satisfy ( ) ( ) ( ) ( 1 3 a a 3 = 3 ⇒ 2a = 3b ⇒ v 4 −3 b b 3 = 2 ) (31.178) and ( 1 3 4 −3 ) ( c d ) ( c = −5 d ) ( 1 ⇒ d = −2c ⇒ v −5 = −2 ) (31.179) Hence y H = c 1 e 3t ( 3 2 ) + c 2 e −5t ( 1 −2 ) (31.180) where c 1 , c 2 are arbitrary constants. Define a matrix U whose columns are the eigenvectors of A. Then Then U = ( 3 1 2 −2 ) where D = diag(3, −5). Hence and U −1 = ( 1/4 1/8 1/4 −3/8 ) (31.181) e At = Ue Dt U −1 (31.182) ( ) ( ) ( ) e At 3 1 e 3t 0 1/4 1/8 = 2 −2 0 e −5t (31.183) 1/4 −3/8 ( ) ( ) 3 1 e = 3t /4 e 3t /8 2 −2 e −5t /4 −3e −5t (31.184) /8 ⎛ 3 ⎜ = ⎝4 e3t + 1 3 4 e−5t 8 e3t − 3 ⎞ 8 e−5t 1 2 e3t − 1 1 2 e−5t 4 e3t + 3 ⎟ ⎠ (31.185) 4 e−5t Since we have e −At = (Ue Dt U −1 ) −1 = Ue −Dt U −1 (31.186) ( ) ( ) ( ) e −At 3 1 e −3t 0 1/4 1/8 = 2 −2 0 e 5t (31.187) 1/4 −3/8 ⎛ 3 ⎜ = ⎝4 e−3t + 1 3 4 e5t 8 e−3t − 3 ⎞ 8 e5t 1 2 e−3t − 1 1 2 e5t 4 e−3t + 3 ⎟ ⎠ (31.188) 4 e5t

325<br />

so that λ = 3, −5. The eigenvectors satisfy<br />

( ) ( ) ( )<br />

(<br />

1 3 a a 3<br />

= 3 ⇒ 2a = 3b ⇒ v<br />

4 −3 b b<br />

3 =<br />

2<br />

)<br />

(31.178)<br />

and<br />

(<br />

1 3<br />

4 −3<br />

) (<br />

c<br />

d<br />

)<br />

( c<br />

= −5<br />

d<br />

)<br />

( 1<br />

⇒ d = −2c ⇒ v −5 =<br />

−2<br />

)<br />

(31.179)<br />

Hence<br />

y H = c 1 e 3t (<br />

3<br />

2<br />

)<br />

+ c 2 e −5t (<br />

1<br />

−2<br />

)<br />

(31.180)<br />

where c 1 , c 2 are arbitrary constants. Def<strong>in</strong>e a matrix U whose columns are<br />

the eigenvectors of A. Then<br />

Then<br />

U =<br />

( 3 1<br />

2 −2<br />

)<br />

where D = diag(3, −5). Hence<br />

and U −1 =<br />

( 1/4 1/8<br />

1/4 −3/8<br />

)<br />

(31.181)<br />

e At = Ue Dt U −1 (31.182)<br />

( ) ( ) ( )<br />

e At 3 1 e<br />

3t<br />

0 1/4 1/8<br />

=<br />

2 −2 0 e −5t (31.183)<br />

1/4 −3/8<br />

( ) ( )<br />

3 1 e<br />

=<br />

3t /4 e 3t /8<br />

2 −2 e −5t /4 −3e −5t (31.184)<br />

/8<br />

⎛<br />

3<br />

⎜<br />

= ⎝4 e3t + 1 3<br />

4 e−5t 8 e3t − 3 ⎞<br />

8 e−5t<br />

1<br />

2 e3t − 1 1<br />

2 e−5t 4 e3t + 3 ⎟<br />

⎠ (31.185)<br />

4 e−5t<br />

S<strong>in</strong>ce<br />

we have<br />

e −At = (Ue Dt U −1 ) −1 = Ue −Dt U −1 (31.186)<br />

( ) ( ) ( )<br />

e −At 3 1 e<br />

−3t<br />

0 1/4 1/8<br />

=<br />

2 −2 0 e 5t (31.187)<br />

1/4 −3/8<br />

⎛<br />

3<br />

⎜<br />

= ⎝4 e−3t + 1 3<br />

4 e5t 8 e−3t − 3 ⎞<br />

8 e5t<br />

1<br />

2 e−3t − 1 1<br />

2 e5t 4 e−3t + 3 ⎟<br />

⎠ (31.188)<br />

4 e5t

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