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Appendix B
| Section B.6
B. Smith-McMillan Forms
B.6 Matrix Fraction Descriptions (MFD)
A model structure that is related to the Smith-McMillan form is
that of a matrix fraction description (MFD). There are
two types, namely a right matrix fraction description (RMFD) and a
left matrix fraction description (LMFD).
We recall that a matrix
and its
Smith-McMillan form
are equivalent matrices. Thus,
there exist two unimodular matrices,
and
,
such
that
![\begin{displaymath}
\ensuremath{\mathbf{G^{SM}}(s)} =\ensuremath{\mathbf{L}(s)}\ensuremath{\mathbf{G}(s)}\ensuremath{\mathbf{R}(s)}\end{displaymath}](appendixb-img88.png) |
(B.6.1) |
This implies that
if
is an
proper transfer-function
matrix, then there exist a
matrix
and
an
matrix
,
such as
![\begin{displaymath}
\ensuremath{\mathbf{G}(s)} =\ensuremath{\mathbf{\tilde{L}}(...
...nsuremath{\mathbf{G^{SM}}(s)}\ensuremath{\mathbf{\tilde{R}}(s)}\end{displaymath}](appendixb-img91.png) |
(B.6.2) |
where
and
are, for example,
given by
![\begin{displaymath}\ensuremath{\mathbf{\tilde{L}}(s)} =[\ensuremath{\mathbf{L}(s...
...ath{\mathbf{\tilde{R}}(s)} =[\ensuremath{\mathbf{R}(s)} ]^{-1}
\end{displaymath}](appendixb-img92.png) |
(B.6.3) |
We next define the following two matrices:
![\begin{displaymath}\ensuremath{\mathbf{N}(s)}\stackrel{\rm\triangle}{=}\diag(\epsilon_1(s),\ldots,\epsilon_r(s),0,\dots,0)
\end{displaymath}](appendixb-img93.png) |
(B.6.4) |
![\begin{displaymath}\ensuremath{\mathbf{D}(s)}\stackrel{\rm\triangle}{=}\diag(\delta_1(s),\ldots,\delta_r(s),1,\dots,1)
\end{displaymath}](appendixb-img94.png) |
(B.6.5) |
where
and
are
matrices.
Hence,
can be written as
![\begin{displaymath}
\ensuremath{\mathbf{G^{SM}}(s)} = \ensuremath{\mathbf{N}(s)} [\ensuremath{\mathbf{D}(s)} ]^{-1}
\end{displaymath}](appendixb-img97.png) |
(B.6.6) |
Combining (B.6.2) and (B.6.6), we can write
![\begin{displaymath}
\ensuremath{\mathbf{G}(s)} =\ensuremath{\mathbf{\tilde{L}}(...
...suremath{\mathbf{G_N}(s)} [\ensuremath{\mathbf{G_D}(s)} ]^{-1}
\end{displaymath}](appendixb-img98.png) |
(B.6.7) |
where
![\begin{displaymath}
\ensuremath{\mathbf{G_N}(s)}\stackrel{\rm\triangle}{=}\ensu...
...uremath{\mathbf{\tilde{R}}(s)} ]^{-1}\ensuremath{\mathbf{D}(s)}\end{displaymath}](appendixb-img99.png) |
(B.6.8) |
Equations (B.6.7) and (B.6.8) define what is
known
as a right matrix fraction description (RMFD)
.
It can be shown that
is always column-equivalent to a
column proper matrix
.
(See definition B.7). This implies that the degree of the pole
polynomial
is equal to the sum of the degrees of the
columns of
.
We also observe that the RMFD is not unique, because, for any nonsingular
matrix
,
we can write
as
![\begin{displaymath}\ensuremath{\mathbf{G}(s)} = \ensuremath{\mathbf{G_N}(s)}\ens...
...suremath{\mathbf{\ensuremath{\boldsymbol{\Omega}}}(s)} ]^{-1}
\end{displaymath}](appendixb-img104.png) |
(B.6.9) |
where
is said to be a right common
factor. When the only right common factors of
and
are unimodular matrices, then, from definition
definition B.7, we have that
and
are
right coprime. In this case, we say
that the RMFD
is irreducible.
It is easy to see that when a RMFD is irreducible, then
Remark B.1 A left matrix fraction description (LMFD)
can be built similarly, with a different grouping of the matrices
in (B.6.7). Namely,
![\begin{displaymath}\ensuremath{\mathbf{G}(s)} =\ensuremath{\mathbf{\tilde{L}}(s)...
...verline{G}_D}(s)} ]^{-1}\ensuremath{\mathbf{\overline{G}_N}(s)}\end{displaymath}](appendixb-img110.png) |
(B.6.10) |
where
![\begin{displaymath}
\ensuremath{\mathbf{\overline{G}_N}(s)}\stackrel{\rm\triang...
...math{\mathbf{D}(s)} [\ensuremath{\mathbf{\tilde{L}}(s)} ]^{-1}
\end{displaymath}](appendixb-img111.png) |
(B.6.11) |
The left and right matrix descriptions have been initially derived
starting from the Smith-McMillan form. Hence, the factors are polynomial
matrices. However, it is immediate to see that they provide a more
general description. In particular,
,
,
and
are generally matrices
with rational entries. One possible way to obtain this type of
representation is to divide the two polynomial matrices forming
the original MFD by the same (stable) polynomial.
An example summarizing the above concepts is considered next.
Example 2.2 Consider a MIMO system having the transfer function
![\begin{displaymath}
\ensuremath{\mathbf{G}(s)} =\begin{bmatrix}\displaystyle{\f...
...ac{1}{s+2}} & \displaystyle{\frac{2}{(s+1)(s+2)}}\end{bmatrix} \end{displaymath}](appendixb-img114.png) |
(B.6.12) |
B.2.1 |
Find the Smith-McMillan form by performing elementary row and column operations.
|
B.2.2 |
Find the poles and zeros.
|
B.2.3 |
Build a RMFD for the model.
|
Solution
B.2.1 |
We first compute its Smith-McMillan form by performing elementary row and
column operations. Referring to equation (B.6.1), we
have that
![\begin{displaymath}
\ensuremath{\mathbf{G^{SM}}(s)} =\ensuremath{\mathbf{L}(s)}...
...{0} & \displaystyle{\frac{s^2+3s+18}{(s+1)(s+2)}} \end{bmatrix}\end{displaymath}](appendixb-img115.png) |
(B.6.13) |
with
![\begin{displaymath}\ensuremath{\mathbf{L}(s)} = \begin{bmatrix}\displaystyle{\fr...
...{8}} \\ [2mm] \displaystyle{0} & \displaystyle{1} \end{bmatrix}\end{displaymath}](appendixb-img116.png) |
(B.6.14) |
|
B.2.2 |
We see that the observable and controllable part of the system has
zero and pole polynomials given by
![\begin{displaymath}p_z(s)=s^2+3s+18; \hspace{20mm}p_p(s)=(s+1)^2(s+2)^2
\end{displaymath}](appendixb-img117.png) |
(B.6.15) |
which, in turn, implies that there are two transmission
zeros, located at
,
and four poles, located at
and .
|
B.2.3 |
We can now build a RMFD by using
(B.6.2).
We first notice
that
![\begin{displaymath}
\ensuremath{\mathbf{\tilde{L}}(s)} =[\ensuremath{\mathbf{L}...
...{8}} \\ [2mm] \displaystyle{0} & \displaystyle{0} \end{bmatrix}\end{displaymath}](appendixb-img121.png) |
(B.6.16) |
Then, using (2.24), with
![\begin{displaymath}
\ensuremath{\mathbf{N}(s)} =\begin{bmatrix}\displaystyle{1}...
...m] \displaystyle{0} &
\displaystyle{(s+1)(s+2)}
\end{bmatrix}\end{displaymath}](appendixb-img122.png) |
(B.6.17) |
the RMFD is obtained from (B.6.7),
(B.6.16), and
(B.6.17), leading to
![\begin{displaymath}\ensuremath{\mathbf{G_N}(s)} =\begin{bmatrix}\displaystyle{4}...
...ystyle{s+1} & \displaystyle{\frac{s^2+3s+18}{8}} \end{bmatrix} \end{displaymath}](appendixb-img123.png) |
(B.6.18) |
and
![\begin{displaymath}\ensuremath{\mathbf{G_D}(s)} =\begin{bmatrix}\displaystyle{1}...
...m]\displaystyle{0} & \displaystyle{(s+1)(s+2)}
\end{bmatrix}
\end{displaymath}](appendixb-img124.png) |
(B.6.19) |
![\begin{displaymath}=\begin{bmatrix}\displaystyle{(s+1)(s+2)} & \displaystyle{\fr...
... \\ \displaystyle{0} & \displaystyle{(s+1)(s+2)} \end{bmatrix} \end{displaymath}](appendixb-img125.png) |
(B.6.20) |
These can then be turned into proper transfer-function matrices by
introducing common stable denominators.
|
|