Root locus method, deriving the position of the asymptote centroid

control theoryroots

In the Root Locus Method, the linear asymptotes are centered at a point on the real axis given by
$$
\sigma_A=\frac{\sum_{j=1}^n(-p_j)-\sum_{i=1}^M(-z_i)}{n-M},
$$

where $p_j$ are the $j$th open-loop poles and $z_i$ are the $i$th open-loop zeros, $n$ and $M$ are the number of open-loop poles and zeros, respectively.

So I was reading about the derivation of the position of the asymptote centroid $\sigma_A$, on Modern Control Systems 20th Edition, by Robert H. Bishop, Page 452 (shown as the following screenshot).

I can't figure out how
$$
\frac{s^M+b_{M-1}s^{M-1}}{s^n+a_{n-1}s^{n-1}}
$$

is reduced into
$$
\frac{1}{s^{n-M}+(a_{n-1}-b_{M-1})s^{n-M-1}}.
$$

Can someone elaborate the reasoning behind this? Please help!

Modern Control Systems 20th Edition, Page 452

Best Answer

This is probably polynomial long-division to two terms, treating the denominator with higher degree (since the Transfer function is proper). In particular, you can verify that the denominator poly $s^n + a_{M-1} s^{n-1} + \dots + a_0$ is equal to $$ (s^{n-M}+(a_{n-1}-b_{M-1})s^{n-M-1})(s^M + b_{M-1} s^{M-1} + \dots + b_0) + O(s^{n-2}) $$ so we can substitute that into our root locus equation to yield $$ 1 + K \frac{s^M + b_{M-1} s^{M-1} + \dots + b_0}{(s^{n-M}+(a_{n-1}-b_{M-1})s^{n-M-1})(s^M + b_{M-1} s^{M-1} + \dots + b_0) + O(s^{n-2})} $$ Dividing through by the numerator gives $$ 1+ K \frac{1}{(s^{n-M}+(a_{n-1}-b_{M-1})s^{n-M-1}) + O(s^{n-M-2})} $$ With that we eliminate the latter, lower order terms to arrive at the desired expression.

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