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Nnamdi Okpala
Nnamdi Okpala

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What is the Laplace Transform?

What is the Laplace Transform?

The Laplace transform is a powerful integral transform that converts a function of time ( t ) (usually ( f(t) )) into a function of a complex frequency variable ( s ), denoted ( F(s) ) or ( \mathcal{L}{f(t)} ).

Definition:
[
F(s) = \mathcal{L}{f(t)} = \int_{0}^{\infty} f(t) \, e^{-st} \, dt
]
where ( s = \sigma + j\omega ) is complex, and the integral converges for ( \Re(s) > \sigma_0 ) (region of convergence).

It acts like a "microscope" that turns differential equations (hard in time domain) into algebraic equations (easy in ( s )-domain).

Key Properties That Make It Useful

Property Time Domain s-Domain Why It's Powerful
Differentiation ( \frac{df}{dt} ) ( s F(s) - f(0^-) ) Turns derivatives into multiplication
Integration ( \int_0^t f(\tau) d\tau ) ( \frac{F(s)}{s} ) Turns integrals into division
Convolution ( f(t) * g(t) ) ( F(s) G(s) ) System response = input × transfer function
Time Shift ( f(t - a) u(t - a) ) ( e^{-as} F(s) ) Handles delays easily
Initial/Final Value ( \lim_{s \to \infty} sF(s) ), ( \lim_{s \to 0} sF(s) ) Quick steady-state checks

Major Applications

  1. Solving Linear Differential Equations (Control Systems & Circuits)
    • Most common use.
    • Example: RLC circuit or mass-spring-damper.
    • Steps:
      1. Take Laplace of entire ODE → algebraic equation.
      2. Solve for ( X(s) ).
      3. Inverse Laplace → time solution ( x(t) ).

Simple Example: Second-order system

[
\ddot{y} + 2\zeta\omega_n \dot{y} + \omega_n^2 y = \omega_n^2 u(t)
]
Laplace →

[
Y(s) = \frac{\omega_n^2}{s^2 + 2\zeta\omega_n s + \omega_n^2} U(s)
]
The fraction is the transfer function ( G(s) ).

  1. Control Systems Engineering

    • Analyze stability (poles of ( G(s) ) in left half-plane → stable).
    • Design controllers (PID, lead-lag) in s-domain.
    • Tools: Bode plots, Nyquist, root locus — all from ( G(j\omega) ).
  2. Signal Processing & Communications

    • System response to arbitrary input: ( Y(s) = H(s) X(s) ).
    • Filters (low-pass, high-pass) designed in s-domain, then converted to digital (bilinear transform).
  3. Heat Transfer, Fluid Dynamics, and PDEs

    • Transform time → solve spatial ODEs.
    • Example: Heat equation in semi-infinite rod → algebraic in s, inverse gives error functions.
  4. Probability & Statistics

    • Moment-generating functions are essentially Laplace transforms.
    • Used in queueing theory, reliability engineering.
  5. Mechanical & Aerospace Engineering

    • Vibration analysis, flutter, servo mechanisms.
    • Transient response without numerical integration.
  6. Power Systems & Electronics

    • Transient analysis of switching circuits.
    • Easier than time-domain simulation for initial conditions.

Why Laplace Over Fourier?

Aspect Fourier Transform Laplace Transform
Frequency domain Pure imaginary ( s = j\omega ) Complex ( s = \sigma + j\omega )
Convergence Requires function to decay sufficiently Handles growing exponentials (via ( \sigma ))
Transients Poor (assumes periodic/steady) Excellent (includes initial conditions)
Causal systems Symmetric Unilateral (t ≥ 0) → perfect for real systems

Fourier is a special case of Laplace on the imaginary axis.

Common Laplace Pairs (You’ll Memorize These)

( f(t) ) ( F(s) )
1 (unit step) ( \frac{1}{s} )
( t ) ( \frac{1}{s^2} )
( e^{-at} ) ( \frac{1}{s + a} )
( \sin(\omega t) ) ( \frac{\omega}{s^2 + \omega^2} )
( \cos(\omega t) ) ( \frac{s}{s^2 + \omega^2} )
( e^{-at} \sin(\omega t) ) ( \frac{\omega}{(s + a)^2 + \omega^2} )

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