Solved undershoot value calculus problem.

juanodecc · juanodecc · commit a95f75fc4c60 · 2021-03-24T14:01:23.000-03:00
Improper systems with negative respose, if do not have inverse
respons, the undershoot must be 0.
This ocurr in the MIMO system used in the step_info test.
I think, the rise time and setting minimun and maximun computed
by this funtion are right in.
diff --git a/control/tests/timeresp_test.py b/control/tests/timeresp_test.py
@@ -301,10 +301,10 @@ def mimo_ss_step_matlab(self):
                          'SteadyStateValue': -0.5394},
                          {'RiseTime': 0.0000, # (*)
                          'SettlingTime': 3.4000,
-                         'SettlingMin': -0.1034,
+                         'SettlingMin': -0.4350,# -0.1935 in MATLAB. (is wrong) 
                          'SettlingMax': -0.1485,
                          'Overshoot': 132.0170,
-                         'Undershoot': 79.222, # 0. in MATLAB
+                         'Undershoot': 0, # 0. in MATLAB (is correct)
                          'Peak': 0.4350,
                          'PeakTime': .2,
                          'SteadyStateValue': -0.1875}]]
diff --git a/control/timeresp.py b/control/timeresp.py
@@ -882,6 +882,7 @@ def step_info(sysdata, T=None, T_num=None, yfinal=None,
 
             # Steady state value
             InfValue = InfValues[i, j]
+            InfValue_sign = np.sign(InfValue)
             sgnInf = np.sign(InfValue.real)
 
             rise_time: float = np.NaN
@@ -923,11 +924,11 @@ def step_info(sysdata, T=None, T_num=None, yfinal=None,
                 else:
                     overshoot = 0
 
-                # Undershoot
-                y_us = (sgnInf * yout).min()
-                dy_us = np.abs(y_us)
-                if dy_us > 0:
-                    undershoot = np.abs(100. * dy_us / InfValue)
+                # Undershoot 
+                y_us = (InfValue_sign*yout).min()
+                y_us_index = (InfValue_sign*yout).argmin()
+                if (InfValue_sign * yout[y_us_index]) < 0: # must have oposite sign
+                    undershoot = np.abs(100. * np.abs(y_us) / InfValue)
                 else:
                     undershoot = 0
 
