Derivation of second order system transfer function

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Discussion Overview

The discussion revolves around the derivation of the transfer function for a second order dynamic system, specifically focusing on a mass-spring-damper system. Participants explore the relationships between input forces, system parameters, and the resulting transfer function, while seeking physical intuition behind the derivation.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Ryan presents a derivation of the transfer function for a second order system, using a mass-spring-damper model and a second-order differential equation.
  • Ryan's approach leads to a transfer function expressed in terms of the input force, while his lecturer's notes present a different formulation involving an input displacement.
  • Ryan concludes that the relationship between the input force and displacement is given by \(\frac{f(t)}{m}=K\omega_n^2x(t)\), but seeks clarification on the physical reasoning behind this conclusion.
  • One participant suggests that unit analysis could provide clarity on the physical intuition behind the relationship.
  • Another participant notes that transfer functions are not dimensionless, as they represent the ratio of output to input, which can have units depending on the specific system being analyzed.

Areas of Agreement / Disagreement

Participants express differing views on the dimensionality of transfer functions and the implications of the relationships derived. There is no consensus on the physical reasoning behind the relationship between force and displacement.

Contextual Notes

Participants discuss the implications of substituting parameters and the dimensionality of the transfer function, indicating that assumptions about the system's parameters may affect the interpretation of the results.

ryan88
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Hi,

I am trying to derive the general transfer function for a second order dynamic system, shown below:

\frac{Y(s)}{X(s)}=\frac{K\omega_n^2}{s^2+2\zeta\omega_ns+\omega_n^2}

In order to do this I am considering a mass-spring-damper system, with an input force of f(t) that satisfies the following second-order differential equation:

m\frac{d^2y}{\dt^2}+c\frac{dy}{dt}+ky=f(t)

Using the following two relationships:

c=2\zeta\omega_nm

\frac{k}{m}=\omega_n^2

I get this:

\frac{d^2y}{dt^2}+2\zeta\omega_n\frac{dy}{dt}+\omega_n^2y=\frac{f(t)}{m}

\mathcal{L}\left\{\frac{d^2y}{dt^2}\right\}+2\zeta\omega_n\mathcal{L}\left\{\frac{dy}{dt}\right\}+\omega_n\mathcal{L}\left\{y\right\}=\frac{1}{m}\mathcal{L}\left\{f(t)\right\}

Y(s)\left[s^2+2\zeta\omega_ns+\omega_n^2\right]=\frac{F(s)}{m}

\frac{Y(s)}{F(s)}=\frac{1}{m(s^2+2\zeta\omega_ns+\omega_n^2)}

Wheras my lecturer has the following in his notes:

\frac{d^2y}{dt^2}+2\zeta\omega_n\frac{dy}{dt}+\omega_n^2y=K\omega_n^2x(t)

\mathcal{L}\left\{\frac{d^2y}{dt^2}\right\}+2\zeta\omega_n\mathcal{L}\left\{\frac{dy}{dt}\right\}+\omega_n\mathcal{L}\left\{y\right\}=K\omega_n^2\mathcal{L}\{x(t)\}

Y(s)\left[s^2+2\zeta\omega_ns+\omega_n^2\right]=K\omega_n^2X(s)

\frac{Y(s)}{X(s)}=\frac{K\omega_n^2}{s^2+2\zeta\omega_ns+\omega_n^2}

This obvisously gives the correct transfer function. So, from the two approaches, I have come to the conclusion that:

\frac{f(t)}{m}=K\omega_n^2x(t)

But I do not understand the physical reasoning behind this. Can anyone offer any help with this?

Thanks,

Ryan
 
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That is standard notation. The "trick" is to multiply the right hand side by \frac{k}{k}. As for physical intuition. Perform a unit analysis. You should be able to draw a clear conclusion from that.
 
Ah yes, I completely missed that. Although substituting \frac{k}{m}=\omega_n^2 leaves the gain of the system as \frac{1}{k} which is then not dimensionless. I thought this transfer function was supposed to be dimensionless?
 
No transfer functions are hardly dimensionless. Transfer functions are the ratio of system \frac{output}{input}. Thus you can see that the transfer function can hold any units as long as it contains the output-input relationship you are looking for.
 
Ok, thanks for your help viscousflow. It is very much appreciated.

Ryan
 

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