SlideShare une entreprise Scribd logo
1  sur  26
Ch 6.4: Differential Equations with
Discontinuous Forcing Functions
In this section focus on examples of nonhomogeneous initial
value problems in which the forcing function is discontinuous.
( ) ( ) 00 0,0),( yyyytgcyybya ′=′==+′+′′
Example 1: Initial Value Problem (1 of 12)
Find the solution to the initial value problem
Such an initial value problem might model the response of a
damped oscillator subject to g(t), or current in a circuit for a
unit voltage pulse.



≥<≤
<≤
=−=
=′==+′+′′
20and50,0
205,1
)()()(
where
0)0(,0)0(),(22
205
tt
t
tututg
yytgyyy
Assume the conditions of Corollary 6.2.2 are met. Then
or
Letting Y(s) = L{y},
Substituting in the initial conditions, we obtain
Thus
)}({)}({}{2}{}{2 205 tuLtuLyLyLyL −=+′+′′
[ ] [ ]
s
ee
yLyysLysyyLs
ss 205
2
}{2)0(}{)0(2)0(2}{2
−−
−
=+−+′−−
( ) ( ) ( ) seeyyssYss ss 2052
)0(2)0(12)(22 −−
−=′−+−++
Example 1: Laplace Transform (2 of 12)
( ) ( ) seesYss ss 2052
)(22 −−
−=++
( )
( )22
)( 2
205
++
−
=
−−
sss
ee
sY
ss
0)0(,0)0(),()(22 205 =′=−=+′+′′ yytutuyyy
We have
where
If we let h(t) = L-1
{H(s)}, then
by Theorem 6.3.1.
)20()()5()()( 205 −−−== thtuthtuty φ
Example 1: Factoring Y(s) (3 of 12)
( )
( ) ( ) )(
22
)( 205
2
205
sHee
sss
ee
sY ss
ss
−−
−−
−=
++
−
=
( )22
1
)( 2
++
=
sss
sH
Thus we examine H(s), as follows.
This partial fraction expansion yields the equations
Thus
Example 1: Partial Fractions (4 of 12)
( ) 2222
1
)( 22
++
+
+=
++
=
ss
CBs
s
A
sss
sH
2/1,1,2/1
12)()2( 2
−=−==⇒
=++++
CBA
AsCAsBA
22
2/12/1
)( 2
++
+
−=
ss
s
s
sH
Completing the square,
Example 1: Completing the Square (5 of 12)
( )
( )
( ) 





++
++
−=






++
+
−=






+++
+
−=




++
+
−=
++
+
−=
16/154/1
4/14/1
2
12/1
16/154/1
2/1
2
12/1
16/1516/12/
2/1
2
12/1
12/
2/1
2
12/1
22
2/12/1
)(
2
2
2
2
2
s
s
s
s
s
s
ss
s
s
ss
s
s
ss
s
s
sH
Thus
and hence
For h(t) as given above, and recalling our previous results,
the solution to the initial value problem is then
Example 1: Solution (6 of 12)
( )
( )
( )
( ) ( ) 





++
−





++
+
−=






++
++
−=
16/154/1
4/15
152
1
16/154/1
4/1
2
12/1
16/154/1
4/14/1
2
12/1
)(
22
2
ss
s
s
s
s
s
sH








−







−== −−−
tetesHLth tt
4
15
sin
152
1
4
15
cos
2
1
2
1
)}({)( 4/4/1
)20()()5()()( 205 −−−= thtuthtutφ
Thus the solution to the initial value problem is
The graph of this solution is given below.
Example 1: Solution Graph (7 of 12)
( ) ( )415sin
152
1
415cos
2
1
2
1
)(
where),20()()5()()(
4/4/
205
teteth
thtuthtut
tt −−
−−=
−−−=φ
The solution to original IVP can be viewed as a composite of
three separate solutions to three separate IVPs:
Example 1: Composite IVPs (8 of 12)
)20()20(),20()20(,022:20
0)5(,0)5(,122:205
0)0(,0)0(,022:50
2323333
22222
11111
yyyyyyyt
yyyyyt
yyyyyt
′=′==+′+′′>
=′==+′+′′<<
=′==+′+′′<≤
Consider the first initial value problem
From a physical point of view, the system is initially at rest,
and since there is no external forcing, it remains at rest.
Thus the solution over [0, 5) is y1 = 0, and this can be verified
analytically as well. See graphs below.
Example 1: First IVP (9 of 12)
50;0)0(,0)0(,022 11111 <≤=′==+′+′′ tyyyyy
Consider the second initial value problem
Using methods of Chapter 3, the solution has the form
Physically, the system responds with the sum of a constant
(the response to the constant forcing function) and a damped
oscillation, over the time interval (5, 20). See graphs below.
Example 1: Second IVP (10 of 12)
205;0)5(,0)5(,122 22222 <<=′==+′+′′ tyyyyy
( ) ( ) 2/14/15sin4/15cos 4/
2
4/
12 ++= −−
tectecy tt
Consider the third initial value problem
Using methods of Chapter 3, the solution has the form
Physically, since there is no external forcing, the response is a
damped oscillation about y = 0, for t > 20. See graphs below.
Example 1: Third IVP (11 of 12)
( ) ( )4/15sin4/15cos 4/
2
4/
13 tectecy tt −−
+=
20);20()20(),20()20(,022 2323333 >′=′==+′+′′ tyyyyyyy
Our solution is
It can be shown that φ and φ' are continuous at t = 5 and t = 20,
and φ'' has a jump of 1/2 at t = 5 and a jump of –1/2 at t = 20:
Thus jump in forcing term g(t) at these points is balanced by a
corresponding jump in highest order term 2y'' in ODE.
Example 1: Solution Smoothness (12 of 12)
)20()()5()()( 205 −−−= thtuthtutφ
-.5072)(lim,-.0072)(lim
2/1)(lim,0)(lim
2020
55
≅′′≅′′
=′′=′′
+−
+−
→→
→→
tt
tt
tt
tt
φφ
φφ
Consider a general second order linear equation
where p and q are continuous on some interval (a, b) but g is
only piecewise continuous there.
If y = ψ(t) is a solution, then ψ and ψ' are continuous on (a, b)
but ψ'' has jump discontinuities at the same points as g.
Similarly for higher order equations, where the highest
derivative of the solution has jump discontinuities at the same
points as the forcing function, but the solution itself and its
lower derivatives are continuous over (a, b).
Smoothness of Solution in General
)()()( tgytqytpy =+′+′′
Find the solution to the initial value problem
The graph of forcing function
g(t) is given on right, and is
known as ramp loading.
( )





≥
<≤−
<≤
=
−
−
−
=
=′==+′′
10,1
10555
50,0
5
10
)(
5
5
)()(
where
0)0(,0)0(),(4
105
t
tt
t
t
tu
t
tutg
yytgyy
Example 2: Initial Value Problem (1 of 12)
Assume that this ODE has a solution y = φ(t) and that φ'(t)
and φ''(t) satisfy the conditions of Corollary 6.2.2. Then
or
Letting Y(s) = L{y}, and substituting in initial conditions,
Thus
( )[ ] ( )[ ] 5}10)({5}5)({}{4}{ 105 −−−=+′′ ttuLttuLyLyL
[ ] 2
105
2
5
}{4)0()0(}{
s
ee
yLysyyLs
ss −−
−
=+′−−
Example 2: Laplace Transform (2 of 12)
( ) ( ) 21052
5)(4 seesYs ss −−
−=+
( )
( )45
)( 22
105
+
−
=
−−
ss
ee
sY
ss
0)0(,0)0(,
5
10
)(
5
5
)(4 105 =′=
−
−
−
=+′′ yy
t
tu
t
tuyy
We have
where
If we let h(t) = L-1
{H(s)}, then
by Theorem 6.3.1.
[ ])10()()5()(
5
1
)( 105 −−−== thtuthtuty φ
Example 2: Factoring Y(s) (3 of 12)
( )
( ) )(
545
)(
105
22
105
sH
ee
ss
ee
sY
ssss −−−−
−
=
+
−
=
( )4
1
)( 22
+
=
ss
sH
Thus we examine H(s), as follows.
This partial fraction expansion yields the equations
Thus
Example 2: Partial Fractions (4 of 12)
( ) 44
1
)( 2222
+
+
++=
+
=
s
DCs
s
B
s
A
ss
sH
4/1,0,4/1,0
144)()( 23
−====⇒
=+++++
DCBA
BAssDBsCA
4
4/14/1
)( 22
+
−=
ss
sH
Thus
and hence
For h(t) as given above, and recalling our previous results,
the solution to the initial value problem is then
Example 2: Solution (5 of 12)
( )ttsHLth 2sin
8
1
4
1
)}({)( 1
−== −






+
−





=
+
−=
4
2
8
11
4
1
4
4/14/1
)(
22
22
ss
ss
sH
[ ])10()()5()(
5
1
)( 105 −−−== thtuthtuty φ
Thus the solution to the initial value problem is
The graph of this solution is given below.
Example 2: Graph of Solution (6 of 12)
[ ]
( )ttth
thtuthtut
2sin
8
1
4
1
)(
where,)10()()5()(
5
1
)( 105
−=
−−−=φ
The solution to original IVP can be viewed as a composite of
three separate solutions to three separate IVPs (discuss):
Example 2: Composite IVPs (7 of 12)
)10()10(),10()10(,14:10
0)5(,0)5(,5/)5(4:105
0)0(,0)0(,04:50
232333
2222
1111
yyyyyyt
yytyyt
yyyyt
′=′==+′′>
=′=−=+′′<<
=′==+′′<≤
Consider the first initial value problem
From a physical point of view, the system is initially at rest,
and since there is no external forcing, it remains at rest.
Thus the solution over [0, 5) is y1 = 0, and this can be verified
analytically as well. See graphs below.
Example 2: First IVP (8 of 12)
50;0)0(,0)0(,04 1111 <≤=′==+′′ tyyyy
Consider the second initial value problem
Using methods of Chapter 3, the solution has the form
Thus the solution is an oscillation about the line (t – 5)/20,
over the time interval (5, 10). See graphs below.
Example 2: Second IVP (9 of 12)
105;0)5(,0)5(,5/)5(4 2222 <<=′=−=+′′ tyytyy
( ) ( ) 4/120/2sin2cos 212 −++= ttctcy
Consider the third initial value problem
Using methods of Chapter 3, the solution has the form
Thus the solution is an oscillation about y = 1/4, for t > 10.
See graphs below.
Example 2: Third IVP (10 of 12)
10);10()10(),10()10(,14 232333 >′=′==+′′ tyyyyyy
( ) ( ) 4/12sin2cos 213 ++= tctcy
Recall that the solution to the initial value problem is
To find the amplitude of the eventual steady oscillation, we
locate one of the maximum or minimum points for t > 10.
Solving y' = 0, the first maximum is (10.642, 0.2979).
Thus the amplitude of the oscillation is about 0.0479.
Example 2: Amplitude (11 of 12)
[ ] ( )ttththtuthtuty 2sin
8
1
4
1
)(,)10()()5()(
5
1
)( 105 −=−−−== φ
Our solution is
In this example, the forcing function g is continuous but g' is
discontinuous at t = 5 and t = 10.
It follows that φ and its first two derivatives are continuous
everywhere, but φ''' has discontinuities at t = 5 and t = 10 that
match the discontinuities of g' at t = 5 and t = 10.
Example 2: Solution Smoothness (12 of 12)
[ ] ( )ttththtuthtuty 2sin
8
1
4
1
)(,)10()()5()(
5
1
)( 105 −=−−−== φ

Contenu connexe

Tendances

Numerical Solution of Ordinary Differential Equations
Numerical Solution of Ordinary Differential EquationsNumerical Solution of Ordinary Differential Equations
Numerical Solution of Ordinary Differential EquationsMeenakshisundaram N
 
Topic: Fourier Series ( Periodic Function to change of interval)
Topic: Fourier Series ( Periodic Function to  change of interval)Topic: Fourier Series ( Periodic Function to  change of interval)
Topic: Fourier Series ( Periodic Function to change of interval)Abhishek Choksi
 
Calculus of variation problems
Calculus of variation   problemsCalculus of variation   problems
Calculus of variation problemsSolo Hermelin
 
Partial Differential Equations, 3 simple examples
Partial Differential Equations, 3 simple examplesPartial Differential Equations, 3 simple examples
Partial Differential Equations, 3 simple examplesEnrique Valderrama
 
Gamma and betta function harsh shah
Gamma and betta function  harsh shahGamma and betta function  harsh shah
Gamma and betta function harsh shahC.G.P.I.T
 
Complex analysis and differential equation
Complex analysis and differential equationComplex analysis and differential equation
Complex analysis and differential equationSpringer
 
Partial differentiation
Partial differentiationPartial differentiation
Partial differentiationTanuj Parikh
 
Inner outer and spectral factorizations
Inner outer and spectral factorizationsInner outer and spectral factorizations
Inner outer and spectral factorizationsSolo Hermelin
 
Limits And Derivative
Limits And DerivativeLimits And Derivative
Limits And DerivativeAshams kurian
 
application of first order ordinary Differential equations
application of first order ordinary Differential equationsapplication of first order ordinary Differential equations
application of first order ordinary Differential equationsEmdadul Haque Milon
 
Chapter3 - Fourier Series Representation of Periodic Signals
Chapter3 - Fourier Series Representation of Periodic SignalsChapter3 - Fourier Series Representation of Periodic Signals
Chapter3 - Fourier Series Representation of Periodic SignalsAttaporn Ninsuwan
 
Calculus of variations & solution manual russak
Calculus of variations & solution manual   russakCalculus of variations & solution manual   russak
Calculus of variations & solution manual russakJosé Pallo
 
Inner Product Space
Inner Product SpaceInner Product Space
Inner Product SpacePatel Raj
 
Numerical Methods
Numerical MethodsNumerical Methods
Numerical MethodsTeja Ande
 
Partial differential equations
Partial differential equationsPartial differential equations
Partial differential equationsaman1894
 

Tendances (20)

Numerical Solution of Ordinary Differential Equations
Numerical Solution of Ordinary Differential EquationsNumerical Solution of Ordinary Differential Equations
Numerical Solution of Ordinary Differential Equations
 
Topic: Fourier Series ( Periodic Function to change of interval)
Topic: Fourier Series ( Periodic Function to  change of interval)Topic: Fourier Series ( Periodic Function to  change of interval)
Topic: Fourier Series ( Periodic Function to change of interval)
 
Gamma function
Gamma functionGamma function
Gamma function
 
Calculus of variation problems
Calculus of variation   problemsCalculus of variation   problems
Calculus of variation problems
 
D021018022
D021018022D021018022
D021018022
 
Partial Differential Equations, 3 simple examples
Partial Differential Equations, 3 simple examplesPartial Differential Equations, 3 simple examples
Partial Differential Equations, 3 simple examples
 
Gamma and betta function harsh shah
Gamma and betta function  harsh shahGamma and betta function  harsh shah
Gamma and betta function harsh shah
 
Complex analysis and differential equation
Complex analysis and differential equationComplex analysis and differential equation
Complex analysis and differential equation
 
Partial differentiation
Partial differentiationPartial differentiation
Partial differentiation
 
Inner outer and spectral factorizations
Inner outer and spectral factorizationsInner outer and spectral factorizations
Inner outer and spectral factorizations
 
Limits And Derivative
Limits And DerivativeLimits And Derivative
Limits And Derivative
 
Furier serice
Furier sericeFurier serice
Furier serice
 
application of first order ordinary Differential equations
application of first order ordinary Differential equationsapplication of first order ordinary Differential equations
application of first order ordinary Differential equations
 
Chapter3 - Fourier Series Representation of Periodic Signals
Chapter3 - Fourier Series Representation of Periodic SignalsChapter3 - Fourier Series Representation of Periodic Signals
Chapter3 - Fourier Series Representation of Periodic Signals
 
Calculus of variations & solution manual russak
Calculus of variations & solution manual   russakCalculus of variations & solution manual   russak
Calculus of variations & solution manual russak
 
Inner Product Space
Inner Product SpaceInner Product Space
Inner Product Space
 
Calculus of variations
Calculus of variationsCalculus of variations
Calculus of variations
 
Numerical Methods
Numerical MethodsNumerical Methods
Numerical Methods
 
Partial differential equations
Partial differential equationsPartial differential equations
Partial differential equations
 
Ma2002 1.13 rm
Ma2002 1.13 rmMa2002 1.13 rm
Ma2002 1.13 rm
 

Similaire à Ch06 4

Similaire à Ch06 4 (20)

Ch03 2
Ch03 2Ch03 2
Ch03 2
 
Applied numerical methods lec14
Applied numerical methods lec14Applied numerical methods lec14
Applied numerical methods lec14
 
Ch06 6
Ch06 6Ch06 6
Ch06 6
 
Testsol
TestsolTestsol
Testsol
 
Ch03 7
Ch03 7Ch03 7
Ch03 7
 
MATLAB sessions Laboratory 6MAT 275 Laboratory 6Forced .docx
MATLAB sessions Laboratory 6MAT 275 Laboratory 6Forced .docxMATLAB sessions Laboratory 6MAT 275 Laboratory 6Forced .docx
MATLAB sessions Laboratory 6MAT 275 Laboratory 6Forced .docx
 
Ch06 2
Ch06 2Ch06 2
Ch06 2
 
Ch03 1
Ch03 1Ch03 1
Ch03 1
 
1520 differentiation-l1
1520 differentiation-l11520 differentiation-l1
1520 differentiation-l1
 
Ch06 3
Ch06 3Ch06 3
Ch06 3
 
Fundamentals of Transport Phenomena ChE 715
Fundamentals of Transport Phenomena ChE 715Fundamentals of Transport Phenomena ChE 715
Fundamentals of Transport Phenomena ChE 715
 
Ep 5512 lecture-02
Ep 5512 lecture-02Ep 5512 lecture-02
Ep 5512 lecture-02
 
Solutions_Manual_to_accompany_Applied_Nu.pdf
Solutions_Manual_to_accompany_Applied_Nu.pdfSolutions_Manual_to_accompany_Applied_Nu.pdf
Solutions_Manual_to_accompany_Applied_Nu.pdf
 
Ch03 4
Ch03 4Ch03 4
Ch03 4
 
Ch03 9
Ch03 9Ch03 9
Ch03 9
 
NotesLaplace.pdf
NotesLaplace.pdfNotesLaplace.pdf
NotesLaplace.pdf
 
Assignment grouping 2(bungee jumping) (edit)
Assignment grouping 2(bungee jumping) (edit)Assignment grouping 2(bungee jumping) (edit)
Assignment grouping 2(bungee jumping) (edit)
 
Ma2002 1.21 rm
Ma2002 1.21 rmMa2002 1.21 rm
Ma2002 1.21 rm
 
Ch02 7
Ch02 7Ch02 7
Ch02 7
 
Automatic Control Via Thermostats Of A Hyperbolic Stefan Problem With Memory
Automatic Control Via Thermostats Of A Hyperbolic Stefan Problem With MemoryAutomatic Control Via Thermostats Of A Hyperbolic Stefan Problem With Memory
Automatic Control Via Thermostats Of A Hyperbolic Stefan Problem With Memory
 

Plus de Rendy Robert (20)

Ch08 3
Ch08 3Ch08 3
Ch08 3
 
Ch07 9
Ch07 9Ch07 9
Ch07 9
 
Ch07 8
Ch07 8Ch07 8
Ch07 8
 
Ch07 7
Ch07 7Ch07 7
Ch07 7
 
Ch07 6
Ch07 6Ch07 6
Ch07 6
 
Ch07 5
Ch07 5Ch07 5
Ch07 5
 
Ch07 4
Ch07 4Ch07 4
Ch07 4
 
Ch07 3
Ch07 3Ch07 3
Ch07 3
 
Ch07 2
Ch07 2Ch07 2
Ch07 2
 
Ch07 1
Ch07 1Ch07 1
Ch07 1
 
Ch06 5
Ch06 5Ch06 5
Ch06 5
 
Ch05 8
Ch05 8Ch05 8
Ch05 8
 
Ch05 7
Ch05 7Ch05 7
Ch05 7
 
Ch05 6
Ch05 6Ch05 6
Ch05 6
 
Ch05 5
Ch05 5Ch05 5
Ch05 5
 
Ch05 4
Ch05 4Ch05 4
Ch05 4
 
Ch05 3
Ch05 3Ch05 3
Ch05 3
 
Ch05 2
Ch05 2Ch05 2
Ch05 2
 
Ch05 1
Ch05 1Ch05 1
Ch05 1
 
Ch04 4
Ch04 4Ch04 4
Ch04 4
 

Ch06 4

  • 1. Ch 6.4: Differential Equations with Discontinuous Forcing Functions In this section focus on examples of nonhomogeneous initial value problems in which the forcing function is discontinuous. ( ) ( ) 00 0,0),( yyyytgcyybya ′=′==+′+′′
  • 2. Example 1: Initial Value Problem (1 of 12) Find the solution to the initial value problem Such an initial value problem might model the response of a damped oscillator subject to g(t), or current in a circuit for a unit voltage pulse.    ≥<≤ <≤ =−= =′==+′+′′ 20and50,0 205,1 )()()( where 0)0(,0)0(),(22 205 tt t tututg yytgyyy
  • 3. Assume the conditions of Corollary 6.2.2 are met. Then or Letting Y(s) = L{y}, Substituting in the initial conditions, we obtain Thus )}({)}({}{2}{}{2 205 tuLtuLyLyLyL −=+′+′′ [ ] [ ] s ee yLyysLysyyLs ss 205 2 }{2)0(}{)0(2)0(2}{2 −− − =+−+′−− ( ) ( ) ( ) seeyyssYss ss 2052 )0(2)0(12)(22 −− −=′−+−++ Example 1: Laplace Transform (2 of 12) ( ) ( ) seesYss ss 2052 )(22 −− −=++ ( ) ( )22 )( 2 205 ++ − = −− sss ee sY ss 0)0(,0)0(),()(22 205 =′=−=+′+′′ yytutuyyy
  • 4. We have where If we let h(t) = L-1 {H(s)}, then by Theorem 6.3.1. )20()()5()()( 205 −−−== thtuthtuty φ Example 1: Factoring Y(s) (3 of 12) ( ) ( ) ( ) )( 22 )( 205 2 205 sHee sss ee sY ss ss −− −− −= ++ − = ( )22 1 )( 2 ++ = sss sH
  • 5. Thus we examine H(s), as follows. This partial fraction expansion yields the equations Thus Example 1: Partial Fractions (4 of 12) ( ) 2222 1 )( 22 ++ + += ++ = ss CBs s A sss sH 2/1,1,2/1 12)()2( 2 −=−==⇒ =++++ CBA AsCAsBA 22 2/12/1 )( 2 ++ + −= ss s s sH
  • 6. Completing the square, Example 1: Completing the Square (5 of 12) ( ) ( ) ( )       ++ ++ −=       ++ + −=       +++ + −=     ++ + −= ++ + −= 16/154/1 4/14/1 2 12/1 16/154/1 2/1 2 12/1 16/1516/12/ 2/1 2 12/1 12/ 2/1 2 12/1 22 2/12/1 )( 2 2 2 2 2 s s s s s s ss s s ss s s ss s s sH
  • 7. Thus and hence For h(t) as given above, and recalling our previous results, the solution to the initial value problem is then Example 1: Solution (6 of 12) ( ) ( ) ( ) ( ) ( )       ++ −      ++ + −=       ++ ++ −= 16/154/1 4/15 152 1 16/154/1 4/1 2 12/1 16/154/1 4/14/1 2 12/1 )( 22 2 ss s s s s s sH         −        −== −−− tetesHLth tt 4 15 sin 152 1 4 15 cos 2 1 2 1 )}({)( 4/4/1 )20()()5()()( 205 −−−= thtuthtutφ
  • 8. Thus the solution to the initial value problem is The graph of this solution is given below. Example 1: Solution Graph (7 of 12) ( ) ( )415sin 152 1 415cos 2 1 2 1 )( where),20()()5()()( 4/4/ 205 teteth thtuthtut tt −− −−= −−−=φ
  • 9. The solution to original IVP can be viewed as a composite of three separate solutions to three separate IVPs: Example 1: Composite IVPs (8 of 12) )20()20(),20()20(,022:20 0)5(,0)5(,122:205 0)0(,0)0(,022:50 2323333 22222 11111 yyyyyyyt yyyyyt yyyyyt ′=′==+′+′′> =′==+′+′′<< =′==+′+′′<≤
  • 10. Consider the first initial value problem From a physical point of view, the system is initially at rest, and since there is no external forcing, it remains at rest. Thus the solution over [0, 5) is y1 = 0, and this can be verified analytically as well. See graphs below. Example 1: First IVP (9 of 12) 50;0)0(,0)0(,022 11111 <≤=′==+′+′′ tyyyyy
  • 11. Consider the second initial value problem Using methods of Chapter 3, the solution has the form Physically, the system responds with the sum of a constant (the response to the constant forcing function) and a damped oscillation, over the time interval (5, 20). See graphs below. Example 1: Second IVP (10 of 12) 205;0)5(,0)5(,122 22222 <<=′==+′+′′ tyyyyy ( ) ( ) 2/14/15sin4/15cos 4/ 2 4/ 12 ++= −− tectecy tt
  • 12. Consider the third initial value problem Using methods of Chapter 3, the solution has the form Physically, since there is no external forcing, the response is a damped oscillation about y = 0, for t > 20. See graphs below. Example 1: Third IVP (11 of 12) ( ) ( )4/15sin4/15cos 4/ 2 4/ 13 tectecy tt −− += 20);20()20(),20()20(,022 2323333 >′=′==+′+′′ tyyyyyyy
  • 13. Our solution is It can be shown that φ and φ' are continuous at t = 5 and t = 20, and φ'' has a jump of 1/2 at t = 5 and a jump of –1/2 at t = 20: Thus jump in forcing term g(t) at these points is balanced by a corresponding jump in highest order term 2y'' in ODE. Example 1: Solution Smoothness (12 of 12) )20()()5()()( 205 −−−= thtuthtutφ -.5072)(lim,-.0072)(lim 2/1)(lim,0)(lim 2020 55 ≅′′≅′′ =′′=′′ +− +− →→ →→ tt tt tt tt φφ φφ
  • 14. Consider a general second order linear equation where p and q are continuous on some interval (a, b) but g is only piecewise continuous there. If y = ψ(t) is a solution, then ψ and ψ' are continuous on (a, b) but ψ'' has jump discontinuities at the same points as g. Similarly for higher order equations, where the highest derivative of the solution has jump discontinuities at the same points as the forcing function, but the solution itself and its lower derivatives are continuous over (a, b). Smoothness of Solution in General )()()( tgytqytpy =+′+′′
  • 15. Find the solution to the initial value problem The graph of forcing function g(t) is given on right, and is known as ramp loading. ( )      ≥ <≤− <≤ = − − − = =′==+′′ 10,1 10555 50,0 5 10 )( 5 5 )()( where 0)0(,0)0(),(4 105 t tt t t tu t tutg yytgyy Example 2: Initial Value Problem (1 of 12)
  • 16. Assume that this ODE has a solution y = φ(t) and that φ'(t) and φ''(t) satisfy the conditions of Corollary 6.2.2. Then or Letting Y(s) = L{y}, and substituting in initial conditions, Thus ( )[ ] ( )[ ] 5}10)({5}5)({}{4}{ 105 −−−=+′′ ttuLttuLyLyL [ ] 2 105 2 5 }{4)0()0(}{ s ee yLysyyLs ss −− − =+′−− Example 2: Laplace Transform (2 of 12) ( ) ( ) 21052 5)(4 seesYs ss −− −=+ ( ) ( )45 )( 22 105 + − = −− ss ee sY ss 0)0(,0)0(, 5 10 )( 5 5 )(4 105 =′= − − − =+′′ yy t tu t tuyy
  • 17. We have where If we let h(t) = L-1 {H(s)}, then by Theorem 6.3.1. [ ])10()()5()( 5 1 )( 105 −−−== thtuthtuty φ Example 2: Factoring Y(s) (3 of 12) ( ) ( ) )( 545 )( 105 22 105 sH ee ss ee sY ssss −−−− − = + − = ( )4 1 )( 22 + = ss sH
  • 18. Thus we examine H(s), as follows. This partial fraction expansion yields the equations Thus Example 2: Partial Fractions (4 of 12) ( ) 44 1 )( 2222 + + ++= + = s DCs s B s A ss sH 4/1,0,4/1,0 144)()( 23 −====⇒ =+++++ DCBA BAssDBsCA 4 4/14/1 )( 22 + −= ss sH
  • 19. Thus and hence For h(t) as given above, and recalling our previous results, the solution to the initial value problem is then Example 2: Solution (5 of 12) ( )ttsHLth 2sin 8 1 4 1 )}({)( 1 −== −       + −      = + −= 4 2 8 11 4 1 4 4/14/1 )( 22 22 ss ss sH [ ])10()()5()( 5 1 )( 105 −−−== thtuthtuty φ
  • 20. Thus the solution to the initial value problem is The graph of this solution is given below. Example 2: Graph of Solution (6 of 12) [ ] ( )ttth thtuthtut 2sin 8 1 4 1 )( where,)10()()5()( 5 1 )( 105 −= −−−=φ
  • 21. The solution to original IVP can be viewed as a composite of three separate solutions to three separate IVPs (discuss): Example 2: Composite IVPs (7 of 12) )10()10(),10()10(,14:10 0)5(,0)5(,5/)5(4:105 0)0(,0)0(,04:50 232333 2222 1111 yyyyyyt yytyyt yyyyt ′=′==+′′> =′=−=+′′<< =′==+′′<≤
  • 22. Consider the first initial value problem From a physical point of view, the system is initially at rest, and since there is no external forcing, it remains at rest. Thus the solution over [0, 5) is y1 = 0, and this can be verified analytically as well. See graphs below. Example 2: First IVP (8 of 12) 50;0)0(,0)0(,04 1111 <≤=′==+′′ tyyyy
  • 23. Consider the second initial value problem Using methods of Chapter 3, the solution has the form Thus the solution is an oscillation about the line (t – 5)/20, over the time interval (5, 10). See graphs below. Example 2: Second IVP (9 of 12) 105;0)5(,0)5(,5/)5(4 2222 <<=′=−=+′′ tyytyy ( ) ( ) 4/120/2sin2cos 212 −++= ttctcy
  • 24. Consider the third initial value problem Using methods of Chapter 3, the solution has the form Thus the solution is an oscillation about y = 1/4, for t > 10. See graphs below. Example 2: Third IVP (10 of 12) 10);10()10(),10()10(,14 232333 >′=′==+′′ tyyyyyy ( ) ( ) 4/12sin2cos 213 ++= tctcy
  • 25. Recall that the solution to the initial value problem is To find the amplitude of the eventual steady oscillation, we locate one of the maximum or minimum points for t > 10. Solving y' = 0, the first maximum is (10.642, 0.2979). Thus the amplitude of the oscillation is about 0.0479. Example 2: Amplitude (11 of 12) [ ] ( )ttththtuthtuty 2sin 8 1 4 1 )(,)10()()5()( 5 1 )( 105 −=−−−== φ
  • 26. Our solution is In this example, the forcing function g is continuous but g' is discontinuous at t = 5 and t = 10. It follows that φ and its first two derivatives are continuous everywhere, but φ''' has discontinuities at t = 5 and t = 10 that match the discontinuities of g' at t = 5 and t = 10. Example 2: Solution Smoothness (12 of 12) [ ] ( )ttththtuthtuty 2sin 8 1 4 1 )(,)10()()5()( 5 1 )( 105 −=−−−== φ