With a little assistance from ChatGPT,

A Bode plot is a graphical representation of the frequency response of a system, which shows how a system responds to input signals of different frequencies. To make a Bode plot of a pendulum, you first need to model the pendulum mathematically as a system that responds to input signals.

Assuming that the pendulum is a simple pendulum, you can model it as a second-order system with a transfer function of the form:

G(s) = K / (s^2 + 2ζωn s + ωn^2)

where K is the gain, ωn is the natural frequency of the pendulum, and ζ is the damping ratio.

To obtain the Bode plot, you can plot the magnitude and phase of the transfer function G(s) as a function of frequency, ranging from 0 to infinity. To do this, you can express the transfer function in terms of frequency by substituting s = jω, where j is the imaginary unit and ω is the frequency in radians per second.

Once you have obtained the transfer function in terms of frequency, you can plot the magnitude and phase of G(jω) as a function of log(ω). The magnitude plot shows how the amplitude of the pendulum's response varies with frequency, while the phase plot shows how the phase of the response varies with frequency.

The Bode plot of a pendulum can provide insights into the system's stability and performance, and can be useful in designing control systems to regulate the pendulum's motion.

python code that will compute the transfer function of a pendulum of a given length and mass. and displays a bode plot

import numpy as np

from scipy import signal

from control import matlab

import matplotlib.pyplot as plt

# Define pendulum parameters

l = 1.0 # length of pendulum in meters

m = 1.0 # mass of pendulum in kilograms

g = 9.81 # acceleration due to gravity in m/s^2

# Compute natural frequency and damping ratio

wn = np.sqrt(g / l)

zeta = 0.05

# Define transfer function

num = [1.0]

den = [1.0, 2*zeta*wn, wn**2]

G = signal.TransferFunction(num, den)

# Compute frequency response

w, mag, phase = signal.bode(G)

# Compute frequency response

# omega = np.logspace(-2, 2, 1000)

# mag, phase, omega = matlab.bode(G, omega)

# Display Bode plot

plt.figure()

plt.semilogx(w , mag)

plt.xlabel('Frequency [rad/s]')

plt.ylabel('Magnitude [dB]')

plt.title('Bode Plot')

plt.grid()

plt.show()

`signal.TransferFunction`

function. It then computes the frequency response using the `matlab.bode`

function and displays the Bode plot using the `matplotlib`

library. You can adjust the values of `l`

, `m`

, and `zeta`

to see how they affect the Bode plot.
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