Drawing the open-loop root locus
Finding the gain using the rlocfind command
Adding a lag controller
Plotting the closed-loop response

From the main problem, the dynamic equations in state-space form are the following:

and the system schematic looks like:

For the original problem setup and the derivation of the above equations and schematic, please refer to the Modeling a DC Motor page.

With a 1 rad/sec step reference, the design criteria are:

Now let's design a controller using the root locus method.

Create a new m-file and type in the following commands (refer to main problem for the details of getting those commands).

J=0.01;
b=0.1;
K=0.01;
R=1;
L=0.5;
A=[-b/J   K/J
   -K/L   -R/L];
B=[0
   1/L];
C=[1   0];
D=0;
[num,den]=ss2tf(A, B, C, D);
num=num(3);

Drawing the open-loop root locus

The main idea of root locus design is to find the closed-loop response from the open-loop root locus plot. Then by adding zeros and/or poles to the original plant, the closed-loop response will be modified. Let's first view the root locus for the plant. Add the following commands at the end of your m-file, then and rerun the file.

rlocus(num,den)
sgrid(.8,0)
sigma(2.3)

Finding the gain using the rlocfind command

If you recall, we need the settling time and the overshoot to be as small as possible. Large damping corresponds to points on the root locus near the real axis. A fast response corresponds to points on the root locus far to the left of the imaginary axis. To find the gain corresponding to a point on the root locus, we can use the rlocfind command. We can find the gain and plot the step response using this gain all at once. To do this, enter the following commands at the end of your m-file and rerun it.

[k,poles] = rlocfind(num,den)
[numc,denc]=cloop(k*num,den,-1);
t=0:0.01:3;
step(numc,denc,t)

selected_point =
  -5.9596 + 2.0513i

k =
   10.0934

poles =
  -6.0000 + 2.0511i
  -6.0000 - 2.0511i

As you can see, the system is overdamped and the settling time is about one second, so the overshoot and settling time requirements. The only problem with this plot is the steady-state error is 0.5. If we increase the gain to reduce the steady-state error, the overshoot condition will not be satisfied. We will have to add a lag controller.

Adding a lag controller

From the plot we see that this is a very simple root locus. The damping or settling time criteria were met with the proportional controller. The steady-state error is the only criteria not met with the proportional controller. A lag compensator can reduce the steady-state error. By doing this, we might however increase our settling time. Try the following lag controller first:

This can be done by changing your m-file to look like the following:

J=0.01;
b=0.1;
K=0.01;
R=1;
L=0.5;
A=[-b/J   K/J
   -K/L   -R/L];
B=[0
   1/L];
C=[1   0];
D=0;

[num,den]=ss2tf(A, B, C, D);
num=num(3);

z1=1;
p1=0.01;
numa = [1 z1];
dena = [1 p1];
numb=conv(num,numa);
denb=conv(den,dena);

rlocus(numb,denb)
sgrid(.8,0)
sigma(2.3)

You should get the following root locus, which looks very similar to the original one:

Plotting the closed-loop response

Now let's close the loop and see the closed-loop step response Enter the following code at the bottom of your m-file:

[k,poles]=rlocfind(numb,denb)
[numc,denc]=cloop(k*numb,denb,-1);
t=0:0.01:3;
step(numc,denc,t)

Your gain should be about 20. As you can see the response is not quite satisfactory. You may also note that even though the gain was selected to correlate with a position close to the damping criteria, the overshoot is not even close to five percent. This is due the the effect of the lag controller kicking in at a later time than the plant. (its pole is slower). What this means is that we can go beyond the dotted lines that represent the limit, and get the higher gains without worrying about the overshoot . Rerun your m-file, place the gain just above the white, dotted line. Keep trying until you get a satisfactory response. It should look similar to the following (we used a gain of around 50):

The steady-state error is smaller than 1%, and the settling time and overshoot requirements have been met. As you can see, the design process for root locus is very much a trial and error process. That is why it is nice to plot the root locus, pick the gain, and plot the response all in one step. If we had not been able to get a satisfactory response by choosing the gains, we could have tried a different lag controller, or even added a lead controller.

Root Locus Examples

Cruise Control | DC Motor | Bus Suspension | Inverted Pendulum

DC Motor Examples

Modeling | PID | Root Locus | Frequency Response | State Space

Tutorials

Basics | Modeling | PID | Root Locus | Frequency Response | State Space | Examples