The Transform Method
. The working table: , , , .
Each entry is one integral. For , when (proved below). The trigonometric entries follow from the same integral through Euler's formula: and are the real and imaginary parts of , whose transform is . The transform weighs by the decaying factor and adds up the result; the figure shows this for at , where the shaded area under is .
: differentiation turns into multiplying by , with the initial condition built in automatically. An initial-value problem becomes algebra in — solve for , split by partial fractions, read the table backward.
Why multiplication by : integrating by parts moves the derivative off and onto , and differentiating brings down the factor ; the boundary term at leaves behind (see the proof below). So every derivative in the equation becomes a power of times plus known initial values.
: since , the inverse transform is . Recognizing table entries inside partial-fraction pieces is the entire skill.
Reading backward is legitimate because two continuous functions with the same transform are equal (Lerch's theorem), so each transform has only one continuous inverse. Constants must match exactly: is because , while would be .
Control theory runs on Laplace: a system's transfer function is the transform of its impulse response, and stability is "poles in the left half-plane" — statements about , not . Circuit analysis, signal processing, and PID controller design all speak this language natively.
(a) Compute . (b) Which function has transform ?
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(a) The transform is linear, so transform term by term: and , giving (valid for ). (b) The sine entry with is , so is the transform of . The cosine entry has in the numerator, so it does not match.
Partial Fractions and the Shift Rule
: a transform in which appears only as inverts to times the inverse of the unshifted function. With partial fractions, the pieces are
- distinct linear factors: , which invert to ;
- a repeated factor: , which inverts to ;
- an irreducible quadratic: complete the square, e.g. , and aim at and .
The shift rule is one line: . Multiplying by an exponential in slides the transform in . That is why completed squares appear: the transform of the damped oscillation is the transform of with replaced by . The repeated-factor entry is the shift rule applied to .
Invert .
Step 1 — write and clear denominators: .
Step 2 — choose to remove one unknown at a time: gives , and gives .
Step 3 — and .
Step 4 — invert with the entry: .
Step 5 — check: , which matches (the initial-value theorem).
Invert .
Step 1 — the denominator has no real roots (), so complete the square: .
Step 2 — rewrite the numerator in terms of : .
Step 3 — split: .
Step 4 — each piece is a table entry with replaced by , i.e. the shift : . Without the shift the inverse would be ; the shift multiplies it by .
Invert .
Step 1 — the factor is repeated, so the form needs both powers: .
Step 2 — clear denominators: . Setting gives ; setting gives .
Step 3 — compare the coefficients: , so .
Step 4 — invert: .
Step 5 — check by transforming back: ✓.
Faced with , it is tempting to match with and answer . But , which has no . Completing the square, , gives . The two are different functions: at , while .
Invert .
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Factor: . Write , so . At : , so . At : , so . Hence . Check: ✓.
Second-Order Problems and Step Responses
For with and , transforming gives
so : the characteristic polynomial sits in the denominator and the initial data in the numerator.
Substitute and and collect the terms: . The roots of are the characteristic roots, so the partial-fraction pieces of over them reproduce the homogeneous solutions, while the poles of produce the particular part. A constant force switched on at has , and its pole at is the new equilibrium.
Solve , , .
Step 1 — transform, with the initial values in place: .
Step 2 — collect: , so .
Step 3 — partial fractions: ; gives and gives .
Step 4 — .
Step 5 — check: ✓ and ✓, and both exponentials are homogeneous solutions, since and are the characteristic roots.
A system at rest obeys for , with .
Step 1 — transform: , so .
Step 2 — partial fractions by covering up each factor and evaluating the rest at its root: at , ; at , ; at , .
Step 3 — , so .
Step 4 — check: ✓, ✓, and ✓.
Step 5 — the system settles at the new equilibrium (where ) without overshooting, because both characteristic roots are real.
Solve for , from rest.
Step 1 — , so .
Step 2 — partial fractions: with (cover-up at ); comparing the and coefficients in gives and .
Step 3 — complete the square: .
Step 4 — invert with the shift rule: .
Step 5 — the overshoot: first vanishes again at , where , about above the final value . The complex roots are what make the response overshoot.
For , , , writing gives , so and , which has , not . The correct transform gives , and . In the transform method the initial values are the only place the data enter; drop them and the solution is lost.
Solve , , , by Laplace transform.
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Transform: , so and . Cover-up: at , ; at , . So and . Check: ✓ and ✓.
Proofs & Why It Matters
Directly: for (the boundary term at dies because ). Setting gives as a corollary.
Integrate by parts: , assuming grows slower than so the boundary term at infinity vanishes.
Iterating gives — initial conditions enter automatically, which is the method's superpower.
Induction with parts: (boundary terms vanish). Unwinding from : .
Going Deeper: Explanations & Worked Problems
Solving an IVP by Laplace is a fixed pipeline. (1) Transform the equation term by term: and fold the initial conditions in at the start — no constants to find later.
(2) Solve the resulting algebraic equation for — always possible, it is linear in . (3) Partial-fraction into table-sized pieces: , quadratic pieces aimed at the sine/cosine entries. (4) Invert with the table. The bookkeeping wins where classical methods strain: piecewise forcing (step functions), impulses, and long chains of initial conditions all ride through the algebra unchanged. The cost is fluency with a small table — and partial fractions, which do the heavy lifting in every problem.
Solve , .
Step 1 — transform both sides: , so .
Step 2 — algebra: .
Step 3 — partial fractions: write ; multiplying out, ; set : ; set : .
So .
Step 4 — invert with the table: .
Step 5 — verify: and ✓, ✓. Compare with the integrating-factor route: same answer, but here the initial condition entered at Step 1 and no constant ever appeared.
Solve , , — deliberately simple, to watch the machinery.
Step 1 — transform: .
Step 2 — solve: .
Step 3 — no partial fractions needed: this is times the table entry .
Step 4 — invert: .
Step 5 — verify: ✓, ✓, ✓. Now the same skeleton with forcing, damping, or a step function only lengthens
Step 3 — the pipeline itself never changes shape, which is exactly its virtue.