A collection of R functions that enables the frequency-domain response analysis (FdRA) of dynamic systems. For a short introduction to FdRA have a look at this blog post.
devtools::install_github("pascalschulthess/freqr")
Takes the coefficients of a transfer function or the matrices A, B, C and D of a linear SISO state space representation and generates a Bode plot.
bodeplot(fr, fr.unit = NULL, n = NULL, d = NULL, A = NULL, B = NULL,
C = NULL, D = NULL, highlight = NULL, label = NULL, as.period = F)
In order to plot the transfer function
s^2 + 0.1s + 7.5
G(s) = ----------------------
s^4 + 0.12s^3 + 9s^2
from 10^0 to 10^1 and add a highlight at 2 [rad/s], the function inputs take the form
bodeplot(fr = c(0, 1),
n = c(1, 0.1, 7.5),
d = c(1, 0.12, 9, 0, 0),
highlight = 2,
label = "Highlight")
and result in
library(pracma)
library(ggplot2)
library(dplyr)
library(grid)
Takes the coefficients of a transfer function and generates a Nyquist plot.
nyquistplot(fr, n = NULL, d = NULL)
In order to plot the transfer function
100
G(s) = ----------------
s^2 + 6s + 100
from 10^-2 to 10^3 the function inputs take the form
nyquistplot(fr = c(-2, 3), n = 100, d = c(1, 6, 100))
and result in
library(pracma)
library(ggplot2)
Take the matrices A, B, C, and D of a linear MIMO state space representation and generate a sigma plot, i.e. a plot of the maximum and minimum singular values of the transfer function matrix evaluated over the frequency range.
sigmaplot(fr, fr.unit = NULL, A = NULL, B = NULL, C = NULL, D = NULL,
as.period = F)
In order to plot the state space represented by
/ 0 1 | 1 0 \
/ A | B \ |-1 -1 | 0 1 |
G(s) = |---|---| = |------|---------|
\ C | D / | 10 0 | 0.1 0 |
\ 0 1 | 0 0.1 /
from 10^-2 to 10^2 the function inputs take the form
sigmaplot(fr = c(-2, 2),
A = matrix(c(0, 1, -1, -1), nrow = 2),
B = diag(2),
C = matrix(c(10, 0, 0, 1), nrow = 2),
D = 0.1*diag(2))
and result in
library(reshape2)
library(ggplot2)