| LTPDA Toolbox™ | contents | ![]() |
We can inject any type of signal in to the simulations. In the previous section we injected sinusoidal siganls. Here we inject noise.
Let's start by making some random noise time-series data:
% Create a noise time-series analysis object to inject
fs = 1/ltp.timestep;
nsecs = 1000;
noise = ao.randn(nsecs, fs);
noise.setName;
% Generate a list of outputs we want from the simulator
outputs = ltp.getPortNamesForBlocks(plist('blocks', {'DELAY_IFO', 'IS'}, 'type', 'outputs'));
% Create the plist to configure simulate
sim_pl = plist('AOS', noise, 'AOS Variable Names', 'TESTSIGNAL.tm1_x', 'return outputs', outputs)
% Run the simulation
out = simulate(ltp, sim_pl);
% Create a plist to configure iplot to plot with subplots
plot_pl = plist('arrangement', 'subplots');
% First extract the internal AOs we want and then plot
o1 = out.getObjectAtIndex(1);
o12 = out.getObjectAtIndex(4);
IS_tm1_x = out.getObjectAtIndex(7);
IS_tm2_x = out.getObjectAtIndex(13);
% Then plot the IFO and IS signals together
iplot(o1, o12, plot_pl);
iplot(IS_tm1_x, IS_tm2_x, plot_pl);
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Simulate LTP with injected signals (no noise) | Estimate tranfser functions from simulated signals, compare with Bode estimates | ![]() |
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