Poles of transfer function and stability

In summary: I was trying to solve for the unknown coefficients in the numerator like (C+1)s, etc. and couldn't get the answer. I guess I need to rest more before doing these problems. Thank you for pointing it out!In summary, the conversation involves a problem in which the matrices for linearized differential equations are solved symbolically, and then the equations are linearized and tabulated. The equations are then recast into two differential equations and transformed using Laplace transforms. The transfer function is derived and analyzed for a step input change, with the conclusion that the system is an integrating system. The conversation also includes a discussion about the difficulty in solving for the transfer function due to a constant term in the denominator,
  • #1
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Homework Statement


upload_2015-9-24_17-51-1.png

upload_2015-9-24_17-51-23.png


Homework Equations

The Attempt at a Solution


part a[/B]
$$ \vec {x} = \left [ \begin{array}{ccc} X-X_{s} \\ S-S_{s} \end{array}
\right ] $$

$$ \vec {u} = \left [ \begin{array}{ccc} S_{0}-S_{0s} \\ \frac {F_{0}}{V}-
\big (\frac {F_{0}}{V} \big )_{s} \end{array} \right ] $$
$$ \vec {y} = \left [ \begin{array}{ccc} X-X_{s} \end{array} \right ] $$
part b
Manipulated input
$$ u_{M} = S_{0}-S_{0s}$$

Disturbance input
$$ u_{D} = \frac {F_{0}}{V}- \big (\frac {F_{0}}{V} \big )_{s} $$
part c
The differential equations
$$ \frac {dX}{dt} = \mu (S) X - \frac {F_{0}}{V}X = f_{1} $$
$$ \frac {dS}{dt} = - \mu(S) \frac {X}{Y} + \frac {F_{0}}{V}(S_{0}-S) =f_{2} $$
are linearized into the form
$$ \dot{\vec{x}} = A \vec {x} + B \vec {u} $$
Where ##A_{ij} = \frac {\partial f_{i}}{\partial x_{j}}## and ##B_{ij} = \frac {\partial f_{i}}{\partial u_{j}}## For example, ##A_{11} = \frac {\partial f_{1}}{\partial X} = \mu(S)-\frac {F_{0}}{V}## and ##B_{11} = \frac {\partial f_{1}}{\partial S_{0}}=0##

The matrices ##A## and ##B## are solved symbolically and the differential equations are linearized below

$$ \left [ \begin{array}{ccc} \frac {d(X-X_{s})}{dt} \\ \frac {d(S-S_{s})}{dt} \end{array} \right ] = \left [ \begin{array}{ccc} \frac
{\mu_{m}S_{s}}{K_{s}+S_{s}}- \big ( \frac {F_{0}}{V} \big )_{s} & \frac {\mu_{m}K_{s}}{(K_{s}+S_{s})^{2}}X_{s} \\ - \frac {\mu_{m}S_{s}}{K_{s}+S_{s}} \cdot \frac {1}{Y} & - \frac {\mu_{m}K_{s}}{(K_{s}+S_{s})^{2}} \frac {X_{s}}{Y} - \big ( \frac {F_{0}}{V} \big )_{s} \end{array} \right ] \left [ \begin{array}{ccc} X-X_{s} \\ S-S_{s} \end{array} \right ] + \left [ \begin{array}{ccc} 0 & -X_{s} \\ \big (\frac {F_{0}}{V} \big )_{s} & S_{0s}-S_{s} \end{array} \right ] \left [ \begin{array}{ccc} S_{0}-S_{0s} \\ \big ( \frac {F_{0}}{V} \big )
- \big ( \frac {F_{0}}{V} \big )_{s} \end{array} \right ] $$

Using the steady state values and parameters given, the equations are linearized and tabulated in
the matrices ##A## and ##B##

$$ \left [ \begin{array}{ccc} \frac {d(X-X_{s})}{dt} \\ \frac
{d(S-S_{s})}{dt} \end{array} \right ] = \left [ \begin{array}{ccc} 7.11 \times 10^{-5} & 0.267 \\
-0.303 & -0.909 \end{array} \right ] \left [ \begin{array}{ccc} X - 1.877 \\
S-0.563 \end{array} \right ] + \left [ \begin{array}{ccc} 0 & -1.877 \\
0.1 & 5.687 \end{array} \right ] \left [ \begin{array}{ccc} S_{0}-6.25 \\ \frac {F_{0}}{V} - 0.1 \end {array} \right ] $$
part d
Recasting the matrices as two differential equations, where ##X = x_{1}## and ##S = x_{2}##,

$$ \frac {dx_{1}}{dt} = 7.11 \times 10^{-5}x_{1} + 0.267 x_{2} -
1.877u_{D} \hspace {2 in} (1)$$

$$ \frac {dx_{2}}{dt} = -0.303x_{1} - 0.909x_{2} + 0.1u_{M}+5.687u_{D} \hspace {1.7 in} (2) $$

Taking the Laplace transform of both differential equations,

$$ sX_{1}(s)= 7.11 \times 10^{-5}X_{1}(s) + 0.267 X_{2}(s) -
1.877U_{D}(s) \hspace {1.25 in} (3)$$

$$ sX_{2}(s) = -0.303X_{1}(s) - 0.909X_{2}(s) + 0.1U_{M}(s)+5.687U_{D}(s) \hspace {0.80 in} (4)$$

Using eq. (3) to solve for##X_{2}(s)= f(X_{1}(s),U_{D}(s))##, we get

$$ X_{2}(s)= 3.745X_{1}(s)(s-7.11 \times 10^{-5})+7.030U_{D}(s) $$

Plug in the expression for ##X_{2}(s)## into equation (4) to eliminate ##X_{2}(s)##. We isolate ##X_{1}(s)##, and the final expression for ##X_{1}(s)= Y(s) = f(U_{D}(s),U_{M}(s))## is

$$ Y(s)= \frac {-7.030(s+0.909)+5.687}{12.360(s-7.11 \times
10^{-5})(s+0.909)+1} U_{D}(s)+ \frac {0.1}{12.360(s-7.11 \times
10^{-5})(s+0.909)+1} U_{M}(s) $$
part e
If the disturbance input, ##\frac {F_{0}}{V}##, were to have a step change of magnitude 0.5, then the transfer function derived in part (d) would have an extra term for ##U_{D}(s)##, which is ##\frac {0.5}{s}##.

$$ Y(s)= \frac {-7.030(s+0.909)+5.687}{12.360(s-7.11 \times
10^{-5})(s+0.909)+1} \cdot \frac {0.5}{s} + \frac {0.1}{12.360(s-7.11 \times
10^{-5})(s+0.909)+1} U_{M}(s) $$

The poles are ##7.11 \times 10^{-5}##, ##-0.909##, and ##0##. With a pole at the origin, and one barely positive, the system is an integrating system and never settles to a steady state when a step input change is made.
part f

Working with only the disturbance input,

$$ Y(s)= \frac {-3.515(s+0.909)+2.844}{12.360s(s-7.11 \times 10^{-5})(s+0.909)+s} $$

I am stuck because my transfer function looks funky, it has the + constant term in the denominator, and I don't think it is right. There should be some (s + a) kind of term, this + s all by itself is something I haven't seen before. The substitution is really ugly for this problem, but I don't think I did it incorrectly. I can't do partial fraction decomposition with that term sticking out there. When I try and solve for ##s = -0.909## or ##s = 7.11 \times 10^{-5}##, I can't get rid of these terms from my transfer function, and then the answer is trivially zero for the constants.

 
Last edited:
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  • #2
Maylis said:
I am stuck because my transfer function looks funky
I don't quite understand why you get stucked.

Just multiply

12.360s(s−7.11×10−5)(s+0.909) = As3 + Bs2 + Cs + D

then add the last s, so that you will get ( C+1 ) instead of C.

Now find the roots in

As3 + Bs2 + (C+1)s + D

rewrite the denominator ( with the roots changed ) and do the partial fraction decomposition.
 
  • #3
Yes, I realized it later. I think I was too tired and hungry and had a headache so I didn't notice
 

Related to Poles of transfer function and stability

What are poles of transfer function?

Poles of transfer function are the values of the variable(s) in a transfer function that make the denominator of the function equal to zero. They represent the locations in the complex plane where the system response becomes unbounded or unstable.

How do poles affect stability of a system?

The location of poles in the complex plane determines the stability of a system. If all the poles are in the left half of the complex plane, the system is stable. If any poles are in the right half of the complex plane, the system is unstable. The closer the poles are to the imaginary axis, the less stable the system becomes.

How can the number of poles be determined from a transfer function?

The number of poles in a transfer function is equal to the order of the denominator polynomial. The highest power of the variable in the denominator polynomial represents the number of poles in the transfer function.

What is the significance of the imaginary axis with respect to poles of transfer function?

The imaginary axis is where the poles of transfer function lie in the complex plane. It is also known as the jω axis. Poles on the imaginary axis result in a marginally stable system, while poles on the imaginary axis and origin result in an unstable system.

How do poles of transfer function affect the frequency response of a system?

The location of poles in the complex plane affects the frequency response of a system. Poles closer to the origin result in a higher magnitude response at low frequencies and a lower magnitude response at high frequencies. Poles farther from the origin result in a more even frequency response. Poles on the imaginary axis result in a flat frequency response.

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