Formulas of Rise time, settling time, and other step-response characteristics for arbitrary-order transfer function
12 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
Andrew Sol
il 16 Ago 2021
Commentato: Star Strider
il 16 Ago 2021
How the parameters of transients are estimated (as in the picture) from an arbitrary linear transfer function (formula is given) ?
0 Commenti
Risposta accettata
Star Strider
il 16 Ago 2021
If you are estimating the transfer function from data, use the System Identification Toolbox functions, specifically iddata and ssest, since it is more robust than tfest, although tfest might be preferable in this instance. Then (if necessary) use the tf function to turn the state space realisation into a transfer function, and then use sys.Numerator and sys.Denominator (for example) to get the coefficients.
2 Commenti
Star Strider
il 16 Ago 2021
I read it carefully. It initially appears to be a system identification and parameter estimation problem:
‘How the parameters of transients are estimated (as in the picture) from an arbitrary linear transfer function (formula is given) ?’
Once the parameters of the transfer function itself are known, it can be modeled as a simplified differential equation (initially in Laplace space, then inverted), and the parameters estimated from it as described in the Wikipedia article on Step response. I am in no way claiming that for an arbitrary stable transfer function it would be a trivial computation, however it would (theoretically, since I have never actually attempted this) be possible.
.
Più risposte (1)
Sulaymon Eshkabilov
il 16 Ago 2021
Use step(), e.g.:
SYS = tf(1, [1 1 2]);
step(SYS)
% Move the cursor over the plot and use the right mouse button options,
% -> characteristics -> Peak time, Settling time, etc.
Vedere anche
Categorie
Scopri di più su Transfer Function Models in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!