Unit 4 · Signals & Systems

Laplace Transform —
Pole-Zero & System Stability

B.Tech ECE · Signals & Systems· ~35 min read· 12 GATE Questions· GATE Weightage: 2–3 marks ⭐
Contents
  1. 1. Why Laplace Transform?
  2. 2. LT Definition & Bilateral vs Unilateral
  3. 3. Region of Convergence (ROC)
  4. 4. Standard LT Pairs
  5. 5. Properties of Laplace Transform
  6. 6. Inverse Laplace Transform (Partial Fractions)
  7. 7. Transfer Function H(s) — Poles & Zeros
  8. 8. BIBO Stability from ROC & Poles
  9. 9. Initial & Final Value Theorems
  10. 10. GATE Questions (12)
Real-World Context — Why Laplace Transform?

Circuit analysis: Solving an RLC circuit with differential equations is hard. LT converts d/dt → s·, ∫dt → 1/s, turning ODEs into algebraic equations in s-domain. Solve in s → take inverse LT → get time response.

Control systems: The transfer function H(s) = Y(s)/X(s) tells you the gain, bandwidth, and stability from just the pole/zero locations — without solving the ODE. Engineers design PID controllers, compensators, and feedback loops entirely in the s-domain.

Filter design: Butterworth, Chebyshev, Bessel filters are all specified by their pole-zero pattern in the s-plane, then converted to hardware using the bilinear transform.

The s-Plane — ROC Regions and System Stability
σ (Real) jω (Imaginary) 0 Left Half-Plane (LHP) Stable poles → Re(s) < 0 e^(σt) decays to 0 Right Half-Plane (RHP) Unstable poles → Re(s) > 0 e^(σt) grows to ∞ jω-axis Marginally stable (poles here) pole (stable) conj. pair pole (unstable) zero ○ ROC of causal signal: Re(s) > σ_max Legend Pole (×) — makes H(s)→∞ Zero (○) — makes H(s)=0 Stable region (LHP) Unstable region (RHP)

The s-plane is the foundation of control and signal processing. Pole locations determine system behavior: LHP poles → stable/decaying response; RHP poles → unstable/growing response; jω-axis poles → sustained oscillation (marginal stability).

1. Why Laplace Transform?

The Fourier Transform requires the signal to be absolutely integrable, which excludes many important signals like ramp, step, and growing exponentials. The Laplace Transform introduces a convergence factor e^(−σt) that forces convergence for a wider class of signals, enabling analysis of unstable systems and transient responses.

Intuition: FT → LT
Fourier Transform: X(jω) = ∫x(t)e^(-jωt)dt [convergence problem for some signals] Laplace Transform: X(s) = ∫x(t)e^(-st)dt where s = σ + jω The e^(-σt) factor provides extra convergence. Setting σ=0 (s=jω) gives back the FT — so the FT is a special case of LT evaluated on the jω-axis.

2. LT Definition & Bilateral vs Unilateral

Bilateral (Two-Sided) Laplace Transform
X(s) = ∫₋∞^∞ x(t) e^(-st) dt where s = σ + jω ∈ ℂ Inverse LT: x(t) = (1/2πj) ∫_{c-j∞}^{c+j∞} X(s) e^(st) ds [Bromwich integral]
Unilateral (One-Sided) Laplace Transform
X(s) = ∫₀₋^∞ x(t) e^(-st) dt [integral starts from 0⁻ to include impulses at t=0] Used for causal signals and circuit analysis (initial conditions via IC terms). ROC: always Re(s) > σ₀ for unilateral LT (right half-plane).

3. Region of Convergence (ROC)

The ROC is the set of s-values for which X(s) = ∫|x(t)e^(−st)|dt converges. It is always a vertical strip in the s-plane and never contains poles.

Signal TypeROCExample
Right-sided (causal): x(t)=0 for t<TRe(s) > σ₀ (right half-plane)e^(−at)u(t) → ROC: Re(s)>−a
Left-sided (anti-causal): x(t)=0 for t>TRe(s) < σ₀ (left half-plane)−e^(−at)u(−t) → ROC: Re(s)<−a
Two-sided (bilateral)σ₁ < Re(s) < σ₂ (vertical strip)e^(−a|t|) → ROC: −a<Re(s)<a
Finite durationEntire s-plane (except possibly s=0,∞)rect(t/τ) → all s
Right-sided with poles at s=−a,−bRe(s) > max(−a, −b)ROC must be to right of all poles
ROC Rules to Remember

1. ROC is a right half-plane for causal signals, left half-plane for anti-causal.
2. ROC never contains poles.
3. FT exists ↔ ROC includes the jω-axis (Re(s)=0).
4. For BIBO stability: ROC of H(s) must include jω-axis → all poles in LHP.

4. Standard Laplace Transform Pairs

x(t) [causal, t≥0]X(s)ROC
δ(t)1All s
u(t)1/sRe(s) > 0
t·u(t) (ramp)1/s²Re(s) > 0
tⁿu(t)n!/s^(n+1)Re(s) > 0
e^(−at)u(t)1/(s+a)Re(s) > −a
t·e^(−at)u(t)1/(s+a)²Re(s) > −a
tⁿe^(−at)u(t)n!/(s+a)^(n+1)Re(s) > −a
sin(ω₀t)u(t)ω₀/(s² + ω₀²)Re(s) > 0
cos(ω₀t)u(t)s/(s² + ω₀²)Re(s) > 0
e^(−at)sin(ω₀t)u(t)ω₀/[(s+a)² + ω₀²]Re(s) > −a
e^(−at)cos(ω₀t)u(t)(s+a)/[(s+a)² + ω₀²]Re(s) > −a
δ(t − T)e^(−sT)All s (T>0)

5. Properties of Laplace Transform

PropertyTime Domain x(t)s-Domain X(s)ROC
Linearityax(t) + by(t)aX(s) + bY(s)ROC_x ∩ ROC_y
Time Shiftingx(t − t₀)u(t−t₀)e^(−st₀)X(s)Same ROC
s-Domain Shiftinge^(−at)x(t)X(s+a)ROC shifted by a
Time Scalingx(at), a>0(1/a)X(s/a)Scaled ROC
Time Reversalx(−t)X(−s)−ROC
Differentiation (time)dx/dtsX(s) − x(0⁻) [unilateral]ROC_x (at min)
Integration (time)∫₀^t x(τ)dτX(s)/sROC_x ∩ {Re(s)>0}
Differentiation (s)−t·x(t)dX(s)/dsROC_x
Convolutionx(t)*h(t)X(s)·H(s)ROC_x ∩ ROC_h
Initial Value Theoremx(0⁺)lim_{s→∞} s·X(s)Causal x(t)
Final Value Theoremx(∞)lim_{s→0} s·X(s)Poles of sX(s) in LHP

Differentiation in Circuit Analysis

Real-Life Example — RLC Circuit in s-Domain

Series RLC circuit: KVL gives: L·di/dt + R·i + (1/C)∫i dt = v_in(t)
Taking LT (unilateral, zero initial conditions):
L·s·I(s) + R·I(s) + (1/Cs)·I(s) = V_in(s)
I(s) = V_in(s) / (Ls + R + 1/Cs)
Transfer function: H(s) = I(s)/V_in(s) = Cs/(LCs² + RCs + 1)

Poles of H(s) = natural frequencies of the RLC circuit. Finding poles tells you whether the circuit rings (complex poles), overdamps (real poles), or has sustained oscillation (poles on jω-axis). No differential equations needed!

6. Inverse Laplace Transform (Partial Fractions)

For rational X(s) = N(s)/D(s), the inverse LT is found by partial fraction expansion (PFE), then using the LT pair table.

Case 1 — Distinct Real Poles

Partial Fraction — Distinct Real Poles
X(s) = N(s)/[(s+p₁)(s+p₂)...(s+pₙ)] = A₁/(s+p₁) + A₂/(s+p₂) + ... + Aₙ/(s+pₙ) Residue formula: Aᵢ = [(s+pᵢ)·X(s)]_{s=−pᵢ} [cover-up method] Each term Aᵢ/(s+pᵢ) → Aᵢ·e^(-pᵢt)u(t) [for causal system, ROC: Re(s)>−pᵢ]

Case 2 — Repeated Poles (order r)

Partial Fraction — Repeated Pole at s = −p
X(s) has pole (s+p)^r: Terms: A_r/(s+p)^r + A_{r-1}/(s+p)^{r-1} + ... + A_1/(s+p) Coefficient: A_k = (1/(r−k)!) · [d^(r-k)/ds^(r-k) · (s+p)^r · X(s)]_{s=−p} LT pair: 1/(s+p)^r → [t^(r-1)/(r-1)!]·e^(-pt)·u(t)

Case 3 — Complex Conjugate Poles

Partial Fraction — Complex Conjugate Poles
Poles at s = −α ± jω₀: Terms group as: (As + B)/[(s+α)² + ω₀²] Using: (s+α)/[(s+α)²+ω₀²] ↔ e^(-αt)cos(ω₀t)u(t) ω₀/[(s+α)²+ω₀²] ↔ e^(-αt)sin(ω₀t)u(t)

7. Transfer Function H(s) — Poles & Zeros

For an LTI system with impulse response h(t), the transfer function is H(s) = LT{h(t)}. It can also be expressed as a rational function:

Transfer Function — General Form
H(s) = Y(s)/X(s) = b_m·(s−z₁)(s−z₂)···(s−z_m) / [a_n·(s−p₁)(s−p₂)···(s−p_n)] Zeros: values of s where H(s) = 0 → z₁, z₂, ..., z_m Poles: values of s where H(s) = ∞ → p₁, p₂, ..., p_n Frequency response: H(jω) = H(s)|_{s=jω} [only valid if jω-axis ∈ ROC]
Pole-Zero Plot Example: Second-Order System H(s) = (s+2)/[(s+1)(s²+2s+5)]
σ -3 -1 +1 +2 +j2 -j2 Zero s = -2 Pole s = -1 s=-1+j2 s=-1-j2 ROC: Re(s) > -1 (to the right of the rightmost pole at s=-1) System is BIBO STABLE All 3 poles have Re(s) = -1 < 0 ROC includes jω-axis ✓ LHP (stable)

All 3 poles (s=-1, s=-1±j2) are in the Left Half-Plane (Re(s)=-1<0). The zero at s=-2 does not affect stability. ROC extends from σ=-1 to +∞, which includes the jω-axis — confirming BIBO stability.

8. BIBO Stability from ROC & Poles

BIBO Stability Conditions
An LTI system with transfer function H(s) is: BIBO Stable: All poles of H(s) in OPEN LHP → Re(pᵢ) < 0 for all i ↔ ROC of H(s) includes the jω-axis Marginally Stable: Poles on jω-axis (Re(pᵢ) = 0), non-repeated ROC touches but may not include jω-axis Unstable: At least one pole in RHP (Re(pᵢ) > 0), OR Repeated pole on jω-axis ROC does NOT include the jω-axis BIBO ↔ |h(t)| is absolutely integrable: ∫₋∞^∞ |h(t)| dt < ∞
Real-Life Example — Stability in Control Systems

Feedback amplifier: H(s) = K/(s+2). Pole at s=−2 (LHP) → stable for any K>0.
Feedback with loop gain: Closed-loop H_cl(s) = KG(s)/(1+KG(s)). If loop gain is too high, poles migrate to RHP → amplifier oscillates (unstable). This is why audio systems howl when the microphone is too close to the speaker.
Motor control: An electric motor's angular velocity response H(s)=1/(Js+B) has a single LHP pole at s=−B/J. Adding a proportional controller K shifts the pole to −(B+K)/J — still stable but faster response. Integral control (adds s=0 pole) → design carefully to avoid instability.

9. Initial & Final Value Theorems

Initial Value Theorem (IVT)
x(0⁺) = lim_{s→∞} [s · X(s)] Conditions: x(t) causal (x(t)=0 for t<0), x(0⁺) exists. Use: Gives x(t) at t=0⁺ without computing inverse LT. Example: X(s) = (s+3)/(s+2)(s+1) x(0⁺) = lim_{s→∞} s · (s+3)/[(s+2)(s+1)] = lim_{s→∞} (s²+3s)/(s²+3s+2) = 1
Final Value Theorem (FVT)
x(∞) = lim_{s→0} [s · X(s)] Conditions: x(t) causal AND all poles of s·X(s) must be in OPEN LHP. (FVT fails if x(t) oscillates or grows unboundedly!) Example: X(s) = 3/[s(s+2)] → all poles of s·X(s) = 3/(s+2) at s=−2 (LHP ✓) x(∞) = lim_{s→0} s · 3/[s(s+2)] = lim_{s→0} 3/(s+2) = 3/2 FAIL case: X(s) = 1/(s²+4) → poles of s·X(s) at ±j2 on jω-axis → FVT invalid (signal is sin(2t), which oscillates, never reaches a final value)
GATE Trap — FVT Validity

FVT gives wrong answer if applied carelessly. Always check: does s·X(s) have all poles in the open LHP? If poles are on the jω-axis or RHP, the FVT cannot be used. Common GATE trap: applying FVT to 1/(s²+ω₀²) and getting 0 — but the actual signal oscillates forever.

GATE PYQs

GATE Questions — Laplace Transform (12)

GATE 2023 2 Marks MCQ
The Laplace transform of x(t) = te^(−3t)u(t) is:
(A) 1/(s+3)²
(B) 1/(s+3)²
(C) 1/(s+3)
(D) 3/(s+3)²

Standard LT pair: t·e^(−at)u(t) ↔ 1/(s+a)² with a = 3.

X(s) = 1/(s+3)², ROC: Re(s) > -3

Answer: (B) 1/(s+3)²

GATE 2022 2 Marks MCQ
A causal LTI system has transfer function H(s) = (s+2)/[(s+1)(s+3)]. The system is:
(A) Stable
(B) Unstable
(C) Marginally stable
(D) Cannot be determined

Poles of H(s) are at s = −1 and s = −3. Both poles have Re(s) < 0 (in LHP).

For a causal system, ROC: Re(s) > −1. This includes the jω-axis.

Answer: (A) Stable — all poles in open LHP, ROC includes jω-axis.

GATE 2021 2 Marks Numerical
For X(s) = (2s+5)/(s²+5s+6), find x(0⁺) using the Initial Value Theorem.
(A) 2
(B) 5/6
(C) 0
(D) 5

IVT: x(0⁺) = lim_{s→∞} s·X(s) = lim_{s→∞} s·(2s+5)/(s²+5s+6)

= lim_{s→∞} (2s²+5s)/(s²+5s+6) = lim_{s→∞} (2 + 5/s)/(1 + 5/s + 6/s²) = 2/1 = 2

Answer: (A) x(0⁺) = 2

GATE 2020 2 Marks MCQ
The ROC of X(s) = 1/(s+2) for a right-sided signal is:
(A) Re(s) > −2
(B) Re(s) < −2
(C) |s| > 2
(D) All s except s = −2

X(s) = 1/(s+2) has a pole at s = −2.

For a right-sided (causal) signal: ROC is to the right of the rightmost pole.

ROC: Re(s) > −2 → corresponds to x(t) = e^(−2t)u(t).

If ROC were Re(s) < −2: x(t) = −e^(−2t)u(−t) [left-sided, anti-causal].

Answer: (A) Re(s) > −2

GATE 2019 2 Marks MCQ
Using the Final Value Theorem, the steady-state value of x(t) for X(s) = 5/[s(s+5)] is:
(A) 0
(B) 5
(C) 1
(D) FVT not applicable

Check FVT applicability: s·X(s) = 5/(s+5). Pole at s = −5 (LHP) ✓ → FVT valid.

x(∞) = lim_{s→0} s · 5/[s(s+5)] = lim_{s→0} 5/(s+5) = 5/5 = 1

x(t) = (1 − e^(−5t))u(t) → x(∞) = 1 ✓

Answer: (C) 1

GATE 2018 2 Marks MCQ
The inverse Laplace transform of X(s) = (2s+3)/[(s+1)(s+2)] is:
(A) (2e^(−t) + e^(−2t))u(t)
(B) (e^(−t) + e^(−2t))u(t)
(C) (e^(−t) − e^(−2t))u(t)
(D) (3e^(−t) − e^(−2t))u(t)

PFE: (2s+3)/[(s+1)(s+2)] = A/(s+1) + B/(s+2)

A = [(s+1)·X(s)]_{s=-1} = (2(-1)+3)/(-1+2) = 1/1 = 1 B = [(s+2)·X(s)]_{s=-2} = (2(-2)+3)/(-2+1) = (-1)/(-1) = 1

X(s) = 1/(s+1) + 1/(s+2) → x(t) = (e^(−t) + e^(−2t))u(t)

Answer: (B) (e^(−t) + e^(−2t))u(t)

GATE 2017 2 Marks MCQ
Which of the following transfer functions represents an unstable system?
(A) H(s) = 1/(s+2)
(B) H(s) = 1/(s−2)
(C) H(s) = s/(s²+2s+2)
(D) H(s) = (s+1)/(s²+3s+2)

(A) Pole at s=−2: LHP → stable

(B) Pole at s=+2: RHP → UNSTABLE

(C) Poles at s=−1±j: LHP → stable

(D) Poles at s=−1, s=−2: LHP → stable

Answer: (B) — pole at s=+2 in RHP → unstable

GATE 2016 2 Marks MCQ
For X(s) = e^(−2s)/(s+1), find x(t):
(A) e^(−t)u(t)
(B) e^(−(t−2))u(t−2)
(C) e^(−2t)u(t−1)
(D) 2e^(−t)u(t−2)

e^(−at)u(t) ↔ 1/(s+a), so 1/(s+1) ↔ e^(−t)u(t)

Time shift property: multiply by e^(−sT) ↔ delay by T in time.

X(s) = e^(-2s) · 1/(s+1) → x(t) = e^(-(t-2))u(t-2)

Signal is zero for t<2, then decays as e^(−(t−2)) for t≥2.

Answer: (B) e^(−(t−2))u(t−2)

GATE 2015 2 Marks MCQ
The LT of cos(ω₀t)u(t) is:
(A) s/(s² + ω₀²)
(B) ω₀/(s² + ω₀²)
(C) 1/(s + jω₀)
(D) s/(s + ω₀²)

Standard pairs: cos(ω₀t)u(t) ↔ s/(s²+ω₀²) and sin(ω₀t)u(t) ↔ ω₀/(s²+ω₀²)

Memory trick: cos starts at amplitude 1 → needs the s in numerator (like derivative). sin starts at 0 → ω₀ in numerator.

Answer: (A) s/(s²+ω₀²)

GATE 2014 2 Marks MCQ
An LTI system with H(s) = 1/(s+a), a>0, has input x(t) = e^(−bt)u(t), b≠a, b>0. The output y(t) is:
(A) [e^(−at) − e^(−bt)]/(b−a) · u(t)
(B) [e^(−at) + e^(−bt)]/(b+a) · u(t)
(C) e^(−(a+b)t)u(t)
(D) t·e^(−at)u(t)

Y(s) = X(s)·H(s) = [1/(s+b)] · [1/(s+a)] = 1/[(s+a)(s+b)]

PFE: 1/[(s+a)(s+b)] = A/(s+a) + B/(s+b) A = 1/(b-a), B = -1/(b-a) = 1/(a-b)

y(t) = [e^(−at) − e^(−bt)]/(b−a) · u(t)

Answer: (A)

GATE 2016 1 Mark MCQ
The differentiation property of the unilateral Laplace Transform states that dx/dt ↔:
(A) sX(s)
(B) sX(s) − x(0⁻)
(C) (1/s)X(s)
(D) jωX(jω)

Unilateral LT differentiation: LT{dx/dt} = sX(s) − x(0⁻)

The initial condition x(0⁻) is subtracted. This allows solving ODEs with initial conditions directly in the s-domain.

For zero initial conditions: LT{dx/dt} = sX(s) (same as bilateral).

Answer: (B) sX(s) − x(0⁻)

GATE 2019 2 Marks Numerical
For X(s) = 3s/(s²+9), is the Final Value Theorem applicable? If yes, what is x(∞)?
(A) 0
(B) 3/9 = 1/3
(C) 3
(D) FVT not applicable

Check: s·X(s) = s · 3s/(s²+9) = 3s²/(s²+9)

Poles of s·X(s): s²+9=0 → s = ±j3. These poles are on the jω-axis — NOT in the open LHP.

FVT condition violated → FVT is NOT applicable.

Actual x(t) = 3·cos(3t)·u(t) — oscillates forever, no final value.

Answer: (D) FVT not applicable (poles of s·X(s) on jω-axis)