LT01E1: First-Order Relaxation
Direct Solution and Laplace-Transform Preview
This companion example follows one simple first-order system through two solution
paths.
The purpose is not yet to teach a transform table. The purpose is to see, in one concrete problem,
why the transform-domain representation is attractive.
Consider the first-order relaxation model
where
- τ > 0 is the time constant,
- K is the steady forcing level,
- y0 is the initial value.
This equation describes the same mathematical structure that appears in first-order
thermal models, simple electrical circuits, mixing problems, and many other relaxation
processes.
Figure 1. A generic first-order relaxation system. The state begins at y0 and approaches the
steady value K with characteristic time scale τ.
1 What should the answer look like before we solve anything?
At steady state, the derivative vanishes:
Equation (1) then gives
So the solution should approach K as time becomes large.
At t = 0, the solution must satisfy
We therefore expect a transient that connects y0 to K.
2 Direct time-domain solution
Divide Equation (1) by τ:
The integrating factor is
Multiply Equation (5) by this factor:
The left side is one derivative:
Integrate from 0 to t:
The integral is
Therefore
Rearrange:
Finally,
Figure 2. Direct time-domain route. Normalize the ODE, choose an integrating factor, combine
the left side into one derivative, integrate, apply the initial value, and simplify.
3 Interpret the direct solution
Equation (13) separates naturally into
The steady part is
The transient is
At t = 0,
As t →∞,
so
The time constant controls how rapidly the transient decays.
At
the transient has been reduced by the factor
Figure 3. First-order relaxation for several initial values with the same K and τ. Every trajectory
approaches the same steady value, while the exponential transient carries the memory of the
initial condition.
4 Now solve the same problem using a Laplace-transform preview
The detailed transform rules will be derived later in the LT series. Here we use two results only to
compare the structure of the calculation.
Let
The derivative property is previewed as
The transform of the constant forcing is
Apply the transform to
Using linearity,
Collect Y (s):
Solve algebraically:
The differential equation has disappeared. The unknown transform Y (s) is now found by ordinary
algebra.
Figure 4. Transform-domain route. The derivative becomes sY − y0, the initial value appears
immediately, and the ODE reduces to an algebraic equation for Y (s).
5 Rewrite the transform so the time-domain pieces are visible
Starting from Equation (28), use
Then
A particularly useful rearrangement is
To verify this, combine the right side:
Multiplying numerator and denominator by τ gives
which matches Equation (28).
Figure 5. Algebraic decomposition of Y (s). The transform separates into a steady term K∕s and a
transient term with denominator s + 1∕τ.
6 Return to the time domain
The two inverse-transform pairs used here are
and
Therefore Equation (31) gives
This is exactly the direct result in Equation (13).
7 Compare the two routes
The direct route required
- normalizing the ODE,
- constructing the integrating factor,
- recognizing a product derivative,
- integrating,
- inserting the initial condition,
- and simplifying.
The transform route required
- transforming the derivative and constant forcing,
- solving an algebraic equation for Y (s),
- rewriting the result into recognizable pieces,
- and taking an inverse transform.
For this very simple problem, the direct method is not inferior. In fact, it is probably
shorter.
The advantage of the transform method becomes clearer when the forcing is delayed, piecewise,
impulsive, or when several initial conditions and higher derivatives appear.
Figure 6. Two routes to the same solution. The direct method emphasizes integration in time; the
Laplace route reorganizes the problem into algebra and then returns to time.
8 A numerical example
Let
Then
At t = 0,
At one time constant,
| y(2) | = 10 − 6e−1 | (40)
|
| ≈ 7.79. | (41) |
At two time constants,
| y(4) | = 10 − 6e−2 | (42)
|
| ≈ 9.19. | (43) |
At three time constants,
| y(6) | = 10 − 6e−3 | (44)
|
| ≈ 9.70. | (45) |
The system approaches K = 10 exponentially.
9 What this example is meant to teach
This example should not yet be memorized as a collection of transform rules.
Its purpose is to make three structural ideas concrete:
- the initial condition enters the transformed equation through the derivative rule,
- the differential equation becomes algebraic in Y (s),
- and the steady and transient parts become recognizable algebraic pieces in the
transform domain.
The remaining LT articles will derive the transform rules that were only previewed
here.
10 Self-check questions
- What is the steady-state value of y in Equation (1)?
- What role does τ play in the time-domain solution?
- Why does the direct solution naturally contain the factor e−t∕τ?
- Where does y0 appear in the transformed equation?
- Why is (τs + 1)Y (s) = K∕s + τy0 easier to manipulate than the original differential
equation?
- What two time-domain pieces correspond to the two terms in Equation (31)?
- Why is the direct method still competitive for this simple example?
- What kinds of forcing functions would make the transform method more attractive?
References
[1] E. Kreyszig, Advanced Engineering Mathematics, Wiley.
[2] R. V. Churchill, Operational Mathematics, McGraw-Hill.