Responses of a transfer function on MATLAB

AI Thread Summary
The discussion focuses on analyzing the stability of a transfer function system represented by the equation (3s + 0.5) / (s^3 + 3s^2 + 8s) using MATLAB. The user attempts to plot the step and ramp responses but encounters instability, despite the roots appearing on the left of the imaginary axis. It is clarified that the presence of a pole at the origin contributes to instability, and a unit feedback system may stabilize it depending on the gain. The response to a ramp input is noted to be a parabola due to the pole at the origin, indicating that the system will not stabilize without adjustments. The conversation concludes with an emphasis on the need for modifications to achieve a stable ramp response.
geft
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I'm given the following system:

\frac { 3s+0.5 }{ { s }^{ 3 }+3{ s }^{ 2 }+8s }

I'm supposed to find the steady state error of the system by plotting the step and ramp responses, and then find the value when s tends to infinity.

Here is the MATLAB code:

Code:
sys1 = 3 + tf(0.5.*[1], [1 0]);
sys2 = tf([1], [1 3 8]);
sys = sys1*sys2

subplot(1, 2, 1)
step(sys)

sys3 = tf([1], [1 0]);
subplot(1, 2, 2)
step(sys*sys3)
title('Ramp Response')

figure
rlocus(sys*sys3)

Here's the result: http://i.imgur.com/vXoXV.png

As can be seen, the step and ramp responses are unstable. All the roots are on the left of the imaginary axis, so the system must be stable. I'm not sure where I went wrong.
 
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geft said:
I'm given the following system:

\frac { 3s+0.5 }{ { s }^{ 3 }+3{ s }^{ 2 }+8s }

I'm supposed to find the steady state error of the system by plotting the step and ramp responses, and then find the value when s tends to infinity.

Here is the MATLAB code:

Code:
sys1 = 3 + tf(0.5.*[1], [1 0]);
sys2 = tf([1], [1 3 8]);
sys = sys1*sys2

subplot(1, 2, 1)
step(sys)

sys3 = tf([1], [1 0]);
subplot(1, 2, 2)
step(sys*sys3)
title('Ramp Response')

figure
rlocus(sys*sys3)

Here's the result: http://i.imgur.com/vXoXV.png

As can be seen, the step and ramp responses are unstable. All the roots are on the left of the imaginary axis, so the system must be stable. I'm not sure where I went wrong.

Your system has a pole at the origin. So, it is unstable. With a unit feedback it can be made stable, depending of the gain (your root locus graph).
 
So it's only stable if it's a closed loop? Thanks, that solved the unit step part.

What about the ramp response? How do I make it stable?
 
Last edited:
The response of a stable system to a ramp input is a ramp, so it tends to infinity.
If you have a pole at the origin, the response to a ramp will be a parabola, as your graph shows.
 
Many thanks for the help.
 
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