Finding Rise Time from System Response

I am trying to find appropriate sample time from the open loop response from my system for use in model predictive control:

A=[-1 1.6 0;0 0 1;0 0 -11.76]; 
B=[0; 0; 1];
C=[50 0 0];
D=zeros(1,1);
Cont_plant=ss(A,B,C,D);       %continuous state space dynamics of plant
step(Cont_plant)

How do i get get the rise time,settling time since this system is not open loop stable? I tried to put it in feedback and still this:

A=[-1 1.6 0;0 0 1;0 0 -11.76]; 
B=[0; 0; 1];
C=[50 0 0];
D=zeros(1,1);
Cont_plant=ss(A,B,C,D);       %continuous state space dynamics of plant
step(Cont_plant)

G=feedback(Cont_plant,1)

G =
 
  A = 
           x1      x2      x3
   x1      -1     1.6       0
   x2       0       0       1
   x3     -50       0  -11.76
 
  B = 
       u1
   x1   0
   x2   0
   x3   1
 
  C = 
       x1  x2  x3
   y1  50   0   0
 
  D = 
       u1
   y1   0
 
Continuous-time state-space model.

step(G)

Answer 1

[Burhan Burak AKMAN]

You can use 'stepinfo' function like below.

A=[-1 1.6 0;0 0 1;0 0 -11.76]; 
B=[0; 0; 1];
C=[50 0 0];
D=zeros(1,1);
Cont_plant=ss(A,B,C,D);       %continuous state space dynamics of plant
step(Cont_plant)

G=feedback(Cont_plant,1);
step(G)

stepinfo(G)

ans = struct with fields:
         RiseTime: 0.4450
    TransientTime: 17.6458
     SettlingTime: 17.6458
      SettlingMin: 0.4255
      SettlingMax: 1.7478
        Overshoot: 74.7832
       Undershoot: 0
             Peak: 1.7478
         PeakTime: 1.3568

[Philip Asante-Mireku]

Is the closed loop response rise time appropriate for use in Model Predictive control for finding prediction horizon and control horizon?