Bode Plot — Transfer Function Analyzer Back
Control Engineering

Bode Plot — Transfer Function Analyzer

Adjust transfer function parameters to generate gain and phase Bode plots in real time. Intuitively experience gain margin, phase margin, and stability criteria for control system design.

System Type

Parameters

s
Stable

Basics of Bode Plot

First-order system: $G(s) = \dfrac{K}{1+\tau s}$
Second-order system: $G(s) = \dfrac{K\omega_n^2}{s^2+2\zeta\omega_n s+\omega_n^2}$
$|G(j\omega)|_{dB} = 20\log_{10}|G(j\omega)|$
Results
Gain Crossover Freq. (rad/s)
Phase crossover frequency (rad/s)
Phase margin (°)
Gain Margin (dB)

Gain plot

Gain

Phase plot

Phase
Theory & Key Formulas

$$G(j\omega) = |G(j\omega)| e^{j\angle G(j\omega)}$$

周波数応答:複素数表現。ゲイン \(|G|\)(dB)と位相 \(\angle G\)(deg)を周波数で表示する。

$$|G(j\omega)|_{dB} = 20\log_{10}|G(j\omega)|$$

ゲイン(dB)変換式。0 dBは倍率1倍、20 dBは10倍、−20 dB/decは1次遅れ傾斜。

$$G_M = -|G(j\omega_{pc})|_{dB}, \quad P_M = 180°+\angle G(j\omega_{gc})$$

ゲイン余裕 \(G_M\)(位相交差周波数での)と位相余裕 \(P_M\)(ゲイン交差周波数での安定余裕)。

💬 Ask the Professor

🙋
What does a Bode plot actually show, and why does it use a logarithmic scale?
🎓
It shows, for each frequency, how much a control system amplifies or attenuates a sinusoidal input and how much phase lag it introduces. The logarithmic scale is used because practical frequency ranges can span many decades, and cascaded gains multiply in linear scale but add in logarithmic scale.
🙋
What happens when phase margin is too small?
🎓
The step response becomes oscillatory. If phase margin falls below about 30 degrees, overshoot becomes large; if it is zero or negative, the system oscillates and becomes unstable. Practical designs often target 45 to 60 degrees of phase margin and at least 6 dB of gain margin. The same idea applies to servo motors, robot arms, and process control.
🙋
How does adding a PID controller change the gain plot?
🎓
The integral term raises low-frequency gain by adding a -20 dB/dec slope, which can drive steady-state error to zero. The derivative term raises high-frequency gain and adds phase lead, increasing phase margin and helping stability. Because it also amplifies high-frequency noise, practical designs limit the derivative time $T_d$.
🙋
Why does dead time make control difficult?
🎓
Dead time $e^{-Ls}$ does not change gain, but it continuously adds phase lag of $-\omega L$ radians. As frequency increases, the phase lag grows and phase margin can collapse. Transport delay is a classic difficulty in chemical plants and distillation columns, where methods such as Smith predictors may be used.

Frequently Asked Questions

The simulator automatically detects the frequency at which the gain plot crosses 0 dB (gain crossover frequency) and the frequency at which the phase plot crosses -180° (phase crossover frequency). The gain margin (the difference between the gain at the phase crossover frequency and 0 dB) and the phase margin (the difference between the phase at the gain crossover frequency and -180°) are displayed. Check these values to assess stability.
The gain of the time delay element e^{-Ls} is constant (0 dB) regardless of frequency, but its phase lags proportionally to frequency. Therefore, when combined with other elements, the phase rotates rapidly in the high-frequency range, reducing the phase margin near the gain crossover frequency. This decreases stability. While the gain plot itself does not oscillate, you can observe the phase plot changing periodically.
Increasing K raises the entire gain plot, shifting the gain crossover frequency to a higher range. This reduces the phase margin, making the system more prone to instability. Conversely, decreasing K increases the phase margin and improves stability, but there is a trade-off as the steady-state error becomes larger. Use the slider to explore appropriate values.
When the damping ratio ζ is small, resonance occurs near the natural angular frequency ω_n, resulting in a sharp peak (resonance peak) in the gain plot. This happens because the system's poles approach the imaginary axis, causing the response to become persistently oscillatory. At ζ=0, the peak theoretically becomes infinite, leading to instability. By lowering ζ to around 0.1 in the simulator, you can observe this phenomenon in real time.

What is Control Bode?

Bode Plot — Transfer Function Analyzer is a fundamental topic in engineering and applied physics. This interactive simulator lets you explore the key behaviors and relationships by directly manipulating parameters and observing real-time results.

By combining numerical computation with visual feedback, the simulator bridges the gap between abstract theory and physical intuition — making it an effective learning tool for students and a rapid-verification tool for practicing engineers.

Physical Model & Key Equations

The simulator is based on the governing equations behind Bode Plot — Transfer Function Analyzer. Understanding these equations is key to interpreting the results correctly.

Each parameter in the equations corresponds to a slider in the control panel. Moving a slider changes the equation's solution in real time, helping you build a direct connection between mathematical expressions and physical behavior.

Real-World Applications

Engineering Design: The concepts behind Bode Plot — Transfer Function Analyzer are applied across mechanical, structural, electrical, and fluid engineering disciplines. This tool provides a quick way to estimate design parameters and sensitivity before committing to full CAE analysis.

Education & Research: Widely used in engineering curricula to connect theory with numerical computation. Also serves as a first-pass validation tool in research settings.

CAE Workflow Integration: Before running finite element (FEM) or computational fluid dynamics (CFD) simulations, engineers use simplified models like this to establish physical scale, identify dominant parameters, and define realistic boundary conditions.

Common Misconceptions and Points of Caution

Model assumptions: The mathematical model used here relies on simplifying assumptions such as linearity, homogeneity, and isotropy. Always verify that your real system satisfies these assumptions before applying results directly to design decisions.

Units and scale: Many calculation errors arise from unit conversion mistakes or order-of-magnitude errors. Pay close attention to the units shown next to each parameter input.

Validating results: Always sanity-check simulator output against physical intuition or hand calculations. If a result seems unexpected, review your input parameters or verify with an independent method.

How to Use

  1. Enter gain constant K (e.g., 2.5 for proportional controller) using kSlider or kVal input field
  2. Set time constant τ (tau) in seconds—typical values range 0.1 to 10s for first-order lag systems
  3. Input natural frequency ωn in rad/s and damping ratio via k2Slider to define second-order dynamics
  4. Observe magnitude and phase curves update in real-time; note gain crossover frequency and phase margin directly on the plot
  5. Adjust wnVal slider to sweep through system resonance and identify bandwidth constraints

Worked Example

Position servo with cascade controller: K=8 (servo gain), τ=0.05s (motor lag), ωn=45 rad/s (actuator resonance), ζ=0.7 (damping ratio via k2Val=0.7). Bode analysis shows magnitude peak of +12 dB at ωn, phase lag reaching −180° near 120 rad/s. Phase margin = 38° at gain crossover 35 rad/s, meeting stability criterion. Reducing K to 4 shifts crossover to 18 rad/s and improves phase margin to 62°.

Practical Notes

  1. For stable closed-loop control, maintain phase margin >30° and gain margin >6 dB; use k2Slider to increase damping if resonance peak exceeds +6 dB
  2. Industrial servo systems typically require ωn between 20–100 rad/s; higher frequencies demand shorter τ values to avoid instability
  3. First-order lag (τ contribution) causes −20 dB/decade roll-off; stacking multiple lags requires lower K to preserve phase margin
  4. Test step response overshoot by noting phase margin value—approximately 60% overshoot corresponds to 20° phase margin