Time response of first and second-order systems

Derives and applies the step response of first- and second-order systems: time constant, damping ratio, natural frequency, rise and peak time, overshoot and settling time.

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Why it matters

Most sensors and loops in instrumentation behave, at least approximately, like first- or second-order systems: a thermometer in a well is first order, a pressure gauge or a galvanometer is second order, and a tuned closed loop is usually designed to look like a second-order system with chosen damping. Rise time, overshoot and settling time are the numbers on a specification sheet, and they come straight from τ, ζ and ωn.

Key ideas

Standard test inputs: step (sudden change of set point), ramp (constant-rate change), impulse (short shock), and sinusoid (frequency response). The step response is the most used because it shows both speed and damping.

First-order system G(s) = K/(τs + 1)

  • One energy store, one pole at s = −1/τ.
  • Step response rises exponentially with no overshoot. After τ it has reached 63.2 % of the final change; after 4τ, 98.2 %; after 5τ, 99.3 %.
  • The initial slope of the step response is K/τ per unit step; if it kept that slope it would reach the final value in exactly τ.
  • For a ramp input the output lags the input by τ in steady state (for K = 1).

Second-order system G(s) = ωn² / (s² + 2ζωn s + ωn²) (unity DC gain)

  • ωn is the undamped natural frequency; ζ is the damping ratio.
  • Poles: s = −ζωn ± ωn√(ζ² − 1).
  • Cases: ζ = 0 undamped (poles on the jω-axis, sustained oscillation at ωn, marginally stable); 0 < ζ < 1 underdamped (complex poles, decaying oscillation at ωd); ζ = 1 critically damped (repeated real pole, fastest response without overshoot); ζ > 1 overdamped (two real poles, sluggish).
  • For underdamped poles, ζωn is the distance of the poles from the jω-axis (sets the decay rate) and ωd is their height (sets the ringing frequency). The angle θ between the pole and the negative real axis satisfies cos θ = ζ.
  • Peak overshoot depends only on ζ. Settling time depends on ζωn.
  • Typical design target: ζ between 0.4 and 0.8, giving about 25 % to 1.5 % overshoot.

Higher-order systems: if one pair of poles is much closer to the jω-axis than the others (roughly five times or more), that dominant pair sets the response and the second-order formulas apply approximately.

Formulas

First order, unit step input:

  • c(t) = K·(1 − e^(−t/τ))
  • t_s (2 %) ≈ 4τ; t_r (10–90 %) = τ·ln 9 ≈ 2.2τ Second order, underdamped, unit step input:
  • ωd = ωn·√(1 − ζ²)
  • c(t) = 1 − [e^(−ζωn t)/√(1 − ζ²)]·sin(ωd t + θ), with θ = cos⁻¹ ζ
  • t_r = (π − θ)/ωd (0 to 100 % rise time)
  • t_p = π/ωd
  • Mp = e^(−πζ/√(1 − ζ²)) (fraction; multiply by 100 for %)
  • ζ = −ln(Mp) / √(π² + ln²(Mp)) (inverse, Mp as a fraction)
  • t_s ≈ 4/(ζωn) (2 % band), t_s ≈ 3/(ζωn) (5 % band)
  • Number of oscillations before settling ≈ t_s·ωd/(2π)

Symbols: K steady-state gain (output unit/input unit), τ time constant (s), ωn, ωd rad/s, ζ dimensionless, θ rad, times in s. Settling-time formulas use the exponential envelope and are approximate; the rest are exact for the standard form with no zeros.

Worked examples

Example 1 — first-order sensor Given: G(s) = 5/(s + 2), unit step input.

  1. Standard form: G(s) = 2.5/(0.5s + 1), so K = 2.5 and τ = 0.5 s.
  2. Final value: c(∞) = K = 2.5.
  3. At t = 1 s: c(1) = 2.5·(1 − e^(−1/0.5)) = 2.5 × (1 − 0.1353) = 2.162.
  4. Settling time (2 %): 4τ = 2.0 s.

Result: τ = 0.5 s, c(∞) = 2.5, c(1 s) = 2.16, t_s ≈ 2.0 s. Note that τ is not the reciprocal of the numerator; it comes from writing the denominator as τs + 1.

Example 2 — unity-feedback position loop (GATE level) Given: G(s) = 25/[s(s + 6)], unity feedback, unit step input.

  1. Closed loop: T(s) = 25/(s² + 6s + 25), so ωn² = 25 → ωn = 5 rad/s and 2ζωn = 6 → ζ = 0.6.
  2. ωd = 5·√(1 − 0.36) = 5 × 0.8 = 4 rad/s; θ = cos⁻¹ 0.6 = 0.927 rad.
  3. Rise time: t_r = (π − 0.927)/4 = 2.214/4 = 0.554 s.
  4. Peak time: t_p = π/4 = 0.785 s.
  5. Overshoot: Mp = e^(−π × 0.6/0.8) = e^(−2.356) = 0.0948, i.e. 9.48 %.
  6. Settling time (2 %): t_s = 4/(ζωn) = 4/3 = 1.33 s.

Result: ωn = 5 rad/s, ζ = 0.6, t_r = 0.554 s, t_p = 0.785 s, Mp = 9.5 %, t_s ≈ 1.33 s.

Common mistakes

  • Reading τ = 1/2 directly from 5/(s + 2) but then using K = 5 instead of 5/2 = 2.5.
  • Using the open-loop transfer function to find ζ and ωn when the question asks about the closed-loop response.
  • Forgetting the phase θ inside the sine of the underdamped response, which makes the response start at the wrong value.
  • Taking θ in degrees inside t_r = (π − θ)/ωd.
  • Believing a higher ωn reduces overshoot: overshoot depends only on ζ.
  • Applying second-order formulas to a system with a nearby zero or a non-dominant pole, where overshoot changes noticeably.

For GATE IN

Expect questions that give G(s) (often in a unity-feedback loop) and ask for ωn, ζ, peak time, overshoot or settling time; questions that give the overshoot or peak time and ask for a gain or ζ; first-order sensor questions on time to reach a percentage of final value or on ramp lag; and pole-location MCQs (which pole pattern gives which response). Practise moving between pole positions, ζ/ωn, and the time-domain numbers.

Quick check

  1. A first-order system with τ = 3 s gets a step. How long until it reaches 95 % of its final value?
  2. For ζ = 0.5, what is the percentage overshoot?
  3. T(s) = 16/(s² + 4s + 16). Find ζ and ωn.
  4. Which two pole parameters set the settling time and the overshoot respectively?

Answers: 1. −3·ln 0.05 = 8.99 s (about 3τ); 2. 16.3 %; 3. ωn = 4 rad/s, ζ = 0.5; 4. Settling time is set by ζωn (real part), overshoot by ζ (pole angle).

Try answering each one aloud before you open it.

  1. 1.What is a first-order system in control systems?Concept

    A first-order system is a dynamic system that can be described by a first-order differential equation. It typically has one energy storage element, such as a capacitor or inductor, and its time response is characterized by a single time constant. The standard form of a first-order system is τ(dy/dt) + y = K·u(t), where τ is the time constant, K is the system gain, and u(t) is the input.

  2. 2.Explain the time response of a first-order system to a step input.Concept

    The time response of a first-order system to a step input is an exponential function. When a step input is applied, the output starts from zero and asymptotically approaches the final value. The response can be described by the equation y(t) = K(1 - e^(-t/τ)), where K is the system gain and τ is the time constant. The time constant τ indicates how quickly the system responds; specifically, it is the time taken for the system to reach approximately 63.2% of its final value.

  3. 3.What is a second-order system in control systems?Concept

    A second-order system is a dynamic system that can be described by a second-order differential equation. It typically has two energy storage elements, such as a combination of capacitors and inductors. The standard form of a second-order system is (d²y/dt²) + 2ζωₙ(dy/dt) + ωₙ²y = ωₙ²u(t), where ζ is the damping ratio, ωₙ is the natural frequency, and u(t) is the input.

  4. 4.Explain the significance of the damping ratio in a second-order system.Concept

    The damping ratio, denoted as ζ, is a dimensionless measure that describes how oscillations in a system decay after a disturbance. It determines the nature of the system's response: if ζ < 1, the system is underdamped and exhibits oscillatory behavior; if ζ = 1, the system is critically damped and returns to equilibrium without oscillating; if ζ > 1, the system is overdamped and returns to equilibrium slowly without oscillating. The damping ratio is crucial for predicting system stability and response speed.

  5. 5.Why is the time constant important in first-order systems?Application

    The time constant, denoted as τ, is important because it indicates the speed of the system's response to changes in input. It is the time required for the system's response to reach approximately 63.2% of its final value after a step input. A smaller time constant means the system responds more quickly, while a larger time constant indicates a slower response. Understanding the time constant helps in designing systems that meet specific performance criteria.

  6. 6.What happens to the response of a second-order system if the damping ratio is zero?Application

    With ζ = 0 the poles sit on the imaginary axis at ±jωn, so the step response is 1 − cos(ωn·t): a sustained oscillation between 0 and 2 at the natural frequency, with no decay. The system is marginally stable — bounded for a step, but any input at ωn makes the output grow without limit. Real systems always have some damping, so ζ = 0 is an idealisation.

  7. 7.How does increasing the damping ratio affect the overshoot in a second-order system?Application

    Increasing the damping ratio ζ in a second-order system generally reduces the overshoot in the system's response to a step input. As ζ increases, the system transitions from underdamped (oscillatory) to critically damped (no overshoot) and eventually to overdamped (slow response with no overshoot). Therefore, a higher damping ratio leads to a more stable response with less overshoot, but it may also slow down the response time.

  8. 8.Calculate the time constant of a first-order system with a transfer function G(s) = 5/(s + 2).Numerical

    The transfer function of a first-order system is generally given by G(s) = K/(τs + 1). Comparing this with G(s) = 5/(s + 2), we can see that τs + 1 = s + 2. Therefore, τ = 1/2 = 0.5 seconds. The time constant of the system is 0.5 seconds.

  9. 9.For a second-order system with a damping ratio ζ = 0.5 and natural frequency ωₙ = 4 rad/s, calculate the damped natural frequency.Numerical

    The damped natural frequency ω_d is given by the formula ω_d = ωₙ√(1 - ζ²). Substituting the given values, ω_d = 4√(1 - 0.5²) = 4√(0.75) = 4 × 0.866 = 3.464 rad/s. The damped natural frequency is 3.464 rad/s.

  10. 10.Why might an engineer choose a critically damped system over an underdamped one?Application

    An engineer might choose a critically damped system because it returns to equilibrium as quickly as possible without oscillating. This is desirable in applications where overshoot and oscillations could be detrimental, such as in precision control systems or systems where stability is critical. A critically damped system provides a balance between speed and stability, ensuring a fast response without the risk of overshoot.

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