Solved root locus exercises, with the loci drawn
Nine exercises with solutions: gain for a damping, asymptotes and breakaway, circular locus, departure angles, stabilising an unstable process, stabilising zero, locus with respect to a parameter, design for overshoot.
Root locus exercises of the kind set in Control Systems courses, in three levels: basic, with second-order systems and gain computation; intermediate, with asymptotes, breakaway points, departure angles and imaginary-axis crossings; exam, with unstable processes, compensation with a zero, locus with respect to a parameter and design to a specification. The result is given straight away; the full solution, with the locus drawn, opens with a click. The proved rules and the MATLAB and Python code are in the in-depth study linked at the top.
Basic level
Exercise 1. The simplest locus
Sketch the locus of
and find the gain for which the closed-loop poles have damping
.
Result: branches on the real axis between 0 and
, breakaway at
for
, then the vertical line
;
.
Solution
Characteristic equation:
. Real axis: the stretch between 0 and
(to the right of each of its points there is one pole). Two asymptotes at
from the centroid
.
Breakaway:
,
, with
. For
the poles are
: the real part stays at
(the sum of the poles is constant, rule 7).
Damping: comparing with
,
and
. For
:
, poles
. Increasing the gain makes the response more oscillatory but not faster to settle: the settling time
s does not change.

Exercise 2. A gain for an overshoot
For
find the gain that gives the dominant poles a damping of 0.5, the position of the third pole and the critical gain.
Result:
; dominant poles
, third pole
;
.
Solution
The dominant poles lie on the line
(damping 0.5, angle 60° from the negative half-axis). By rule 7, the sum of the three poles is always
: if the dominant ones are
, the third is
.
Requiring
, the coefficient of
gives
, i.e.
,
. Then the dominant poles are
, the third
, and
.
Critical gain (Routh, or
):
,
,
. The gain margin with
is
.
The third pole is seven times further from the axis than the dominant ones: its influence is small, and the actual overshoot (15.5 %) is close to that of the second-order system (16.3 %).

Intermediate level
Exercise 3. Four poles: asymptotes, breakaway, stability
For
find the asymptotes, the breakaway points and the critical gain.
Result: centroid
, angles
and
; breakaway at
and
(both with
);
with
.
Solution
Real axis: stretches
and
. Asymptotes:
, centroid
, angles
.
Breakaway:
,
: roots
,
,
. The point
is not on the locus (between
and
there are two poles to the right, an even number). At the other two
: the same
by symmetry (the poles are symmetric about
).
Routh on
: second row
; third
and
; fourth
, positive for
. Auxiliary equation
:
.

Exercise 4. The circular locus and maximum damping
For
find the breakaway points and the gain that gives maximum damping of the complex poles.
Result: breakaway at
and
; maximum damping
for
, with poles
.
Solution
Breakaway (in-depth study):
,
.
The complex part of the locus is the circle centred at
with radius
. The damping of a pole is the cosine of the angle between the line to the origin and the negative half-axis: it is maximum where the line from the origin is tangent to the circle. There
,
, and the distance from the origin is
.
The pole is
. From the equation
, the real part is
, so
. Check:
has roots
.

Exercise 5. Departure angle and crossing
For
compute the departure angle from the pole
, the asymptotes and the critical gain.
Result:
; centroid
, angles
,
;
with
.
Solution
Departure (rule 6):
.
Asymptotes:
.
Characteristic equation
. Routh:
, i.e.
. For
:
,
.
Check with rule 7: for
the poles are
and the third must be
(sum
): indeed
. ✓

Exam level
Exercise 6. Stabilising an unstable process
The process
is controlled with a gain
in unity feedback. For which
is the closed loop stable? For which
are the poles real and coincident?
Result: stable for
; coincident poles for
, at
(and for
, at
, unstable).
Solution
Characteristic equation:
. Stable if all coefficients are positive:
.
Coincident poles: zero discriminant,
,
,
. For
the double root is
: the breakaway on the left, on the stretch to the left of the zero. For
the root is
, between the two unstable poles: a breakaway in the right half-plane.
The locus is a circle centred at
with radius
:
are exactly
and
. ✓

Exercise 7. A stabilising zero
To the system
, unstable for
, a zero at
is added:
. Show that the closed loop is now stable for every
.
Result: vertical asymptotes with centroid
; Routh always satisfied.
Solution
Asymptotes:
, angles
, centroid
. The branches going to infinity stay on the line
, in the left half-plane.
Routh on
: all coefficients positive, and the third-order condition
holds for every
(it becomes
).
The zero is obtained with a PD controller,
, or in practice with a lead network (zero followed by a pole much further to the left, which leaves the picture almost unchanged).

Exercise 8. The locus with respect to damping
The mass-spring-damper system
has adjustable damping
. Sketch the path of the poles as
varies and find
for critical damping and for
.
Result: the poles move on the circle
; critical damping for
;
for
.
Solution
Characteristic equation
, rewritten as
: a locus with poles
and a zero at 0 (in-depth study).
As long as the poles are complex, their product is 4, so
: they lie on the circle of radius
. With
:
. Critical damping
for
(poles coincident at
);
for
, poles
.

Exercise 9. Design to an overshoot specification
The process
is controlled with a gain
. Find
for a 10 % overshoot and the corresponding settling time. Write the MATLAB and Python commands to check it.
Result:
,
;
s.
Solution
From the overshoot:
.
Characteristic equation
:
,
, so
and
. Poles
.
2 % settling time:
s, fixed by the real part
, which a gain alone cannot move. For a faster system a zero is needed (lead network) to bring the locus further left.
Check in MATLAB: G = tf(1,[1 5 0]); stepinfo(feedback(17.9*G,1)). In Python: ct.step_info(ct.feedback(17.9*ct.tf([1],[1,5,0]),1)), which gives an overshoot of 10.0 % and a settling time of 1.42 s: the formula
is a conservative estimate, obtained from the exponential envelope.




