When you do transfer function math like this, matlab doesn't attempt to deal with poles and zeros that should cancel. Then you can run into problems when the pole/zero cancellations that should be exact but aren't because of rounding errors. You can see from your expression for Gcl that Gcl should have a third order denominator. But Gcl as computed is:
>> Gcl
Gcl =
3.2 s^4 + 4 s^3 - 5.6 s^2 - 1.6 s
---------------------------------------
s^6 + 2 s^5 + 0.2 s^4 - 1.6 s^2 - 1.6 s
Continuous-time transfer function.
Now look at the poles and zeros:
>> [p,z]=pzmap((Gcl))
p =
0.0000 + 0.0000i
-2.0000 + 0.0000i
1.0000 + 0.0000i
-0.1107 + 1.0076i
-0.1107 - 1.0076i
-0.7785 + 0.0000i
z =
0
-2.0000
1.0000
-0.2500
Note that the first three poles seem to be equivalent to the first three zeros. Mathematically, they should be. But are they numerically:
>> [z(1:3)-p(1:3)].'
ans =
1.0e-15 *
0 0 -0.8882
So we see that third pole at s=1 doesn't perfectly cancel with the zero. As a result, your step response will eventually go unstable. If you're confident that the those three poles and zeros should cancel based on your problem, you can do:
>> minreal(Gcl)
ans =
3.2 s + 0.8
-----------------------
s^3 + s^2 + 1.2 s + 0.8
Continuous-time transfer function.
Which is probably the answer you're looking for. Or, you could have gotten that answer directly using:
>> feedback(Gr*G,1)
ans =
3.2 s + 0.8
-----------------------
s^3 + s^2 + 1.2 s + 0.8
Continuous-time transfer function.
