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The Bode plot for a linear, time-invariant system with transfer function (being the complex frequency in the Laplace domain) consists of a magnitude plot and a phase plot. The Bode magnitude plot is the graph of the function | H ( s = j ω ) | {\displaystyle |H(s=j\omega )|} of frequency ω {\displaystyle \omega } (with j {\displaystyle j ...
The root locus plots the poles of the closed loop transfer function in the complex s-plane as a function of a gain parameter (see pole–zero plot). Evans also invented in 1948 an analog computer to compute root loci, called a "Spirule" (after "spiral" and " slide rule "); it found wide use before the advent of digital computers .
It is also possible to perform Monte Carlo sensitivity analysis. The plotting tool is capable of generating frequency spectrums and performing frequency analysis to generate Bode diagrams and Nyquist plots. Hopsan models can be exported to Simulink. Plot data can be exported to XML, CSV, gnuplot and Matlab.
Magnitude transfer function of a bandpass filter with lower 3 dB cutoff frequency f 1 and upper 3 dB cutoff frequency f 2 Bode plot (a logarithmic frequency response plot) of any first-order low-pass filter with a normalized cutoff frequency at =1 and a unity gain (0 dB) passband.
# set terminal svg enhanced size 875 1250 fname "Times" fsize 25 set terminal postscript enhanced portrait dashed lw 1 "Helvetica" 14 set output "bode.ps" # ugly part of something G(w,n) = 0 * w * n + 100000 # 1 / (sqrt(1 + w**(2*n))) dB(x) = 0 + x + 100000 # 20 * log10(abs(x)) P(w) = w * 0 + 200 # -atan(w)*180/pi # Gridlines set grid # Set x axis to logarithmic scale set logscale x 10 set ...
Bode's sensitivity integral, discovered by Hendrik Wade Bode, is a formula that quantifies some of the limitations in feedback control of linear parameter invariant systems. Let L be the loop transfer function and S be the sensitivity function. In the diagram, P is a dynamical process that has a transfer function P(s).
This page was last edited on 19 July 2005, at 14:41 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may ...
The top row is a series of plots using the escape time algorithm for 10000, 1000 and 100 maximum iterations per pixel respectively. The bottom row uses the same maximum iteration values but utilizes the histogram coloring method. Notice how little the coloring changes per different maximum iteration counts for the histogram coloring method plots.