Simply decompose to N(s)/D(s) + A(s), where order of N(s) <= order of D(s).The problem in implementing this e.g. in Matlab is, that the inverse transfer function would have more zeros than poles which leads to an error.
What do you want to mean ?The output is just an array of values
Even if output is just an array of values, there is no problem.The output is just an array of values
Yes.Since any of the transfer functions I estimated has zeros in the right half plane, I guess the approach with the transfer function in the negative feedback is not going to work, because the will turn into poles and cause unbounded oscillations. Correct?
If one of them is unstable, the whole will be unstable.I did also try a Simulink model with input->transfer function->inverse transfer function-> recover input signal. If I however plug in any other signal into the inverse transfer function the ouput will oscillate again.
Does this mean that for my circuit it is impossible to apply the inverse transfer function to the output in order to recover the input signal?
twig27 said:In my case
I have a transfer function of the form H(s) = 1/(s^3+a*s^2+b*s+c).
The inverse would just be the polynomial.
How can I simulate that in Matlab?
dt=2*pi/1000;
t=[0:dt:2*pi];
x=sin(t);
size(x) ->> 1, 1001
x1=diff(x)/dt
x2=diff(x1)/dt
x3=diff(x2)/dt
size(x1) ->> 1, 1000
size(x2) ->> 1, 999
size(x3) ->> 1, 998
y = x3(1:end) + x2(2:end) + x1(3:end) + x(4:end)
>> plot(x, 'r')
>> hold on, grid on
>> plot(x1, 'c')
>> plot(x2, 'g')
>> plot(x3, 'y')
Show me input signal and reconstructed output signal.however there are problems when I try reconstruct a signal containing high freuquencies.
The reconstructed signal exhibits strong oscillations.
Are there certain constraints with regard to time resolution?
It is no more than linear differential and integral equation problem.Could you recommend any literature on this?
Periodic signal or whatever signal?Consider a decomposition of an input signal to low frequency and high frequency components.
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