Skip to content Skip to navigation

Connexions

You are here: Home » Content » CT Linear Systems and Differential Equations

Navigation

Recently Viewed

This feature requires Javascript to be enabled.

Tags

(What is a tag?)

These tags come from the endorsement, affiliation, and other lenses that include this content.

CT Linear Systems and Differential Equations

Module by: Michael Haag. E-mail the author

User rating (How does the rating system work?)
Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

:
(0 ratings)

Summary: The module discusses how to represent linear, time-invariant systems.

Note: Your browser may not currently support MathML. See our browser support page for additional details. You can always view the correct math in the PDF version.

Note: You are viewing an old version of this document. The latest version is available here.

Continuous-Time Linear Systems

Physically realizable, linear time-invariant systems can be described by a set of linear differential equations (LDEs):

Figure 1: Graphical description of a basic linear time-invariant system with an input, ft f t and an output, yt y t .
Figure 1 (ctlin.png)

dndtnyt+ a n 1 dn1dtn1yt++ a 1 ddtyt+ a 0 yt= b m dmdtmft++ b 1 ddtft+ b 0 ft n t y t a n 1 n 1 t y t a 1 t y t a 0 y t b m m t f t b 1 t f t b 0 f t Equivalently,

i=0n a i didtiyt=i=0m b i didtift i n 0 a i i t y t i m 0 b i i t f t (1)
with a n =1 a n 1 .

It is easy to show that these equations define a system that is linear and time invariant. A natural question to ask, then, is how to find the system's output response yt y t to an input ft f t . Recall that such a solution can be written as yt= y i t+ y s t y t y i t y s t We refer to y i t y i t as the zero-input response -- the homogeneous solution due only to the initial conditions of the system. We refer to y s t y s t as the zero-state response -- the particular solution in response to the input ft f t . We now discuss how to solve for each of these components of the system's response.

Finding the Zero-Input Response

The zero-input response, y i t y i t , is the system response due to initial conditions only.

Example 1: Zero-Input Response

Put a voltage across the capacitor in the circuit pictured below and then leave everything else alone.

Figure 2:
Figure 2 (image1.png)

Example 2: Zero-Input Response

Imagine a mass attached to a spring, as shown below. When you pull the mass down and let it go, you have an example of a zero-input response.

Figure 3: The dog displayed in this picture is enjoying a comfortable bed.
Figure 3 (image1.png)

There is no input, so we solve for y 0 t y 0 t such that

a n , a n =1:i=0n a i didti y 0 t=0 a n a n 1 i n 0 a i i t y 0 t 0 (2)
If DD is the derivative operator, we can write the previous equation as:
Dn+ a n 1 Dn1++ a 0 y 0 t=0 D n a n 1 D n 1 a 0 y 0 t 0 (3)
Since we need the weighted sum of a bunch of y 0 t y 0 t 's derivatives to be 00 for all tt, then y 0 tddt y 0 td2dt2 y 0 t y 0 t t y 0 t 2 t y 0 t must all be of the same form.

Only the exponential, st s t where s s , has this property (see your Differential Equation's textbook for details). So we must assume that,

c,c0: y 0 t=cst c c 0 y 0 t c s t (4)
for some cc and ss.

Since ddt y 0 t=csst t y 0 t c s s t , d2dt2 y 0 t=cs2st 2 t y 0 t c s 2 s t , … we have Dn+ a n 1 Dn1++ a 0 y 0 t=0 D n a n 1 D n 1 a 0 y 0 t 0

csn+ a n 1 sn1++ a 1 s+ a 0 st=0 c s n a n 1 s n 1 a 1 s a 0 s t 0 (5)
Equation 5 holds for all tt only when
sn+ a n 1 sn1++ a 1 s+ a 0 =0 s n a n 1 s n 1 a 1 s a 0 0 (6)
Where this equation is referred to as the characteristic equation of the system. The possible values of ss are the roots of this polynomial s 1 s 2 s n s 1 s 2 s n s s 1 s s 2 s s 3 s s n =0 s s 1 s s 2 s s 3 s s n 0 i.e. possible solutions are c 1 s 1 t c 1 s 1 t , c 2 s 2 t c 2 s 2 t , , c n s n t c n s n t . Since the system is linear, the general solution if of the form:
y 0 t= c 1 s 1 t+ c 2 s 2 t++ c n s n t y 0 t c 1 s 1 t c 2 s 2 t c n s n t (7)
Then, solve for the c 1 c n c 1 c n using the initial conditions.

Example 3

See Lathi p.108 for a good example!

We generally assume that the IC's of a system are zero, which implies y i t=0 y i t 0 . However, the method of solving for y i t y i t will prove useful later on.

Finding the Zero-State Response

Solving a linear differential equation

i=0n a i didtiyt=i=0m b i didtift i n 0 a i i t y t i m 0 b i i t f t (8)
given a specific input ft f t is a difficult task in general. More importantly, the method depends entirely on the nature of ft f t ; if we change the input signal, we must completely re-solve the system of equations to find the system response.

Convolution helps to bypass these difficulties. In section 2, we explain how convolution helps to determine the system's output, given only the input ft f t and the system's impulse response, ht h t .

Before deriving the convolution procedure, we show that a system's impulse response is easily derived from its linear, differential equation (LDE). We will show the derivation for the LDE below, where m<n m n :

dndtnyt+ a n 1 dn1dtn1yt++ a 1 ddtyt+ a 0 yt= b m dmdtmft++ b 1 ddtft+ b 0 ft n t y t a n 1 n 1 t y t a 1 t y t a 0 y t b m m t f t b 1 t f t b 0 f t (9)
We can rewrite Equation 9 as
Q D yt= P D ft Q D y t P D f t (10)
where Q D · Q D · is an operator that maps yt y t to the left hand side of Equation 9
Q D yt=dndtnyt+ a n 1 dn1dtn1yt++ a 1 ddtyt+ a 0 yt Q D y t n t y t a n 1 n 1 t y t a 1 t y t a 0 y t (11)
and P D · P D · maps ft f t to the right hand side of Equation 9. Lathi shows (in Appendix 2.1) that the impulse response of the system described by Equation 9 is given by:
ht= b n δt+ P D y n tμt h t b n δ t P D y n t μ t (12)
where for m<n m n we have b n =0 b n 0 . Also, y n y n equals the zero input response with initial conditions. y n 1 0=1 y n 2 0=1y0=0 y n 1 0 1 y n 2 0 1 y 0 0

Content actions

Give Feedback:

E-mail the module author | Rate module ( How does the rating system work?)

Rating system

Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

(0 ratings)

Download:

Add module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections directly in Connexions. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need a Connexions account to use 'My Favorites'.

| A lens (?)

Definition of a lens

Lenses

A lens is a custom view of Connexions content. You can think of it as a fancy kind of list that will let you see Connexions through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to Connexions materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual Connexions member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks