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Automatic Controls 1

The root locus

Magnitude and angle conditions, sketching rules, asymptotes and breakaway points, a complete three-pole example, choosing the gain and the effect of an added zero.

As the gain of a proportional controller is increased, the closed-loop poles move in the complex plane: they start from the plant poles and, beyond a certain value, may cross the imaginary axis. The root locus is the drawing of these paths. It is sketched with a few rules, without solving high-degree equations, and shows at a glance which behaviours a simple gain can achieve and which need a more elaborate controller.

The definition

Let L(s) = K\,\frac{N(s)}{D(s)}, with N of degree m (zeros z_i) and D of degree n \ge m (poles p_i). The closed-loop poles are the roots of

    \[ D(s) + K\,N(s) = 0 \]

The root locus is the set of these roots as K goes from 0 to +\infty.

The magnitude and angle conditions. A point s belongs to the locus if and only if N(s)/D(s) = -1/K, that is

    \[ \sum_i \arg(s - z_i) - \sum_i \arg(s - p_i) = 180° + k\cdot 360°,\qquad K = \frac{\prod|s - p_i|}{\prod|s - z_i|} \]

The angle condition decides where the locus lies, the magnitude condition which gain corresponds to each point.

Sketching rules

  1. The locus has n branches, symmetric about the real axis.
  2. The branches start at the poles of L (K = 0) and end at the zeros (K \to \infty); n - m branches go to infinity.
  3. On the real axis, the points belonging to the locus are those with an odd number of real poles and zeros to their right (from the angle condition: each pole or zero to the right contributes 180°, those to the left 0°, complex pairs cancel).
  4. Branches going to infinity follow asymptotes with angles \frac{180° + k\cdot 360°}{n - m}, starting from the centroid

    \[ \sigma_a = \frac{\sum p_i - \sum z_i}{n - m} \]

  1. Two branches meeting on the real axis break away at the points where \frac{d}{ds}\frac{D(s)}{N(s)} = 0 (breakaway points).
  2. Crossings of the imaginary axis are found with the Routh criterion.

A complete example

    \[ L(s) = \frac{K}{s(s + 2)(s + 4)} \]

Three poles (0, −2, −4), no zeros.

  • Real axis: the segment between 0 and −2 (one pole to the right) and everything to the left of −4 (three poles) belong to the locus.
  • Asymptotes: n - m = 3, angles 60°, 180°, 300°, centroid \sigma_a = (0 - 2 - 4)/3 = -2.
  • Breakaway: D(s) = s^3 + 6s^2 + 8s, D'(s) = 3s^2 + 12s + 8 = 0 gives s \approx -0.845 (the other root, −3.15, is not on the locus). There K = |s||s + 2||s + 4| \approx 3.08.
  • Imaginary axis: from the lesson on stability, K = 48 and s = \pm j2\sqrt2.
Root locus of K/(s(s+2)(s+4))
The three open-loop poles are the crosses at 0, −2 and −4. Two branches start from 0 and −2, meet at the breakaway point near −0.85 and leave the real axis following the ±60° asymptotes from −2; they cross the imaginary axis at ±j2√2. The third branch starts from −4 and goes towards −∞ along the real axis.

Reading the plot. For K \lt 3.08 the poles are real: a response without oscillation but slow. Between 3.08 and 48 the dominant pair is complex and less and less damped. For damping \zeta = 0.5 (16% overshoot) the poles must lie on the line at 60° from the negative real axis: the locus meets it at K \approx 8.3, with poles at -0.67 \pm j1.15; the third pole is at -4.67, seven times further away, and the pair is truly dominant. The settling time is then about 4/0.67 \approx 6 s, and it cannot be reduced by changing the gain alone: the real part of the complex poles never goes further left than −2, the centroid of the asymptotes.

Reshaping the locus

This is where the method is useful in design. Adding a zero to the controller attracts the branches and moves them to the left: with a zero at −2.5, for example, the asymptotes become two at ±90° with centroid (-6 + 2.5)/2 = -1.75, and the loop stays stable for any gain. This is the effect of derivative action and of lead networks. Adding a pole (like the integrator) pushes the branches to the right and reduces stability. The root locus makes this trade-off visible, which is why, even in the age of simulation software, it remains the tool for reasoning about design.

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