fix citations and references

murrayrm · murrayrm · commit d498ad52045b · 2025-02-02T21:14:17.000-08:00
diff --git a/control/delay.py b/control/delay.py
@@ -26,16 +26,20 @@ def pade(T, n=1, numdeg=None):
 
     Returns
     -------
-    num, den : array
+    num, den : ndarray
         Polynomial coefficients of the delay model, in descending powers of s.
 
     Notes
     -----
-    Based on:
-      1. Algorithm 11.3.1 in Golub and van Loan, "Matrix Computation" 3rd.
-         Ed. pp. 572-574
-      2. M. Vajta, "Some remarks on Padé-approximations",
-         3rd TEMPUS-INTCOM Symposium
+    Based on [1]_ and [2]_.
+
+    References
+    ----------
+    .. [1] Algorithm 11.3.1 in Golub and van Loan, "Matrix Computation" 3rd.
+         Ed. pp. 572-574.
+
+    .. [2] M. Vajta, "Some remarks on Padé-approximations",
+         3rd TEMPUS-INTCOM Symposium.
 
     Examples
     --------
diff --git a/control/modelsimp.py b/control/modelsimp.py
@@ -259,12 +259,13 @@ def balanced_reduction(sys, orders, method='truncate', alpha=None):
 
     States are eliminated based on Hankel singular value.  If `sys` has
     unstable modes, they are removed, the balanced realization is done on
-    the stable part, then reinserted in accordance with the reference
-    below.
+    the stable part, then reinserted in accordance with [1]_.
 
-    Reference: Hsu,C.S., and Hou,D., 1991,
-    Reducing unstable linear control systems via real Schur transformation.
-    Electronics Letters, 27, 984-986.
+    References
+    ----------
+    .. [1] C. S. Hsu and D. Hou, "Reducing unstable linear control
+       systems via real Schur transformation".  Electronics Letters,
+       27, 984-986, 1991.
 
     Parameters
     ----------
@@ -479,8 +480,7 @@ def eigensys_realization(arg, r, m=None, n=None, dt=True, transpose=False):
     References
     ----------
     .. [1] Samet Oymak and Necmiye Ozay, Non-asymptotic Identification of
-       LTI Systems from a Single Trajectory.
-       https://arxiv.org/abs/1806.05722
+       LTI Systems from a Single Trajectory. https://arxiv.org/abs/1806.05722
 
     Examples
     --------
diff --git a/control/passivity.py b/control/passivity.py
@@ -293,9 +293,11 @@ def ispassive(sys, ofp_index=0, ifp_index=0):
 
     References
     ----------
-    .. [1] McCourt, Michael J., and Panos J. Antsaklis
-          "Demonstrating passivity and dissipativity using computational
-          methods."
+
+    .. [1] McCourt, Michael J., and Panos J. Antsaklis "Demonstrating
+       passivity and dissipativity using computational methods."
+       Technical Report of the ISIS Group at the University of Notre
+       Dame.  ISIS-2013-008, Aug. 2013.
 
     """
     return solve_passivity_LMI(sys, rho=ofp_index, nu=ifp_index) is not None
diff --git a/control/rlocus.py b/control/rlocus.py
@@ -218,8 +218,8 @@ def _default_gains(num, den, xlim, ylim):
 
     References
     ----------
-    Ogata, K. (2002). Modern control engineering (4th ed.). Upper
-    Saddle River, NJ : New Delhi: Prentice Hall..
+    .. [1] Ogata, K. (2002). Modern control engineering (4th
+       ed.). Upper Saddle River, NJ : New Delhi: Prentice Hall..
 
     """
     # Compute the break points on the real axis for the root locus plot
diff --git a/control/statesp.py b/control/statesp.py
@@ -1069,24 +1069,30 @@ def feedback(self, other=1, sign=-1):
         return StateSpace(A, B, C, D, dt)
 
     def lft(self, other, nu=-1, ny=-1):
-        """Return the Linear Fractional Transformation.
+        """Return the linear fractional transformation.
 
         A definition of the LFT operator can be found in Appendix A.7,
-        page 512 in the 2nd Edition, Multivariable Feedback Control by
-        Sigurd Skogestad.
-
-        An alternative definition can be found here:
+        page 512 in [1]_.  An alternative definition can be found here:
         https://www.mathworks.com/help/control/ref/lft.html
 
         Parameters
         ----------
-        other : LTI
+        other : `StateSpace`
             The lower LTI system.
         ny : int, optional
             Dimension of (plant) measurement output.
         nu : int, optional
             Dimension of (plant) control input.
 
+        Returns
+        -------
+        `StateSpace`
+
+        References
+        ----------
+        .. [1] S. Skogestad, Multivariable Feedback Control.  Second
+           edition, 2005.
+
         """
         other = _convert_to_statespace(other)
         # maximal values for nu, ny
diff --git a/control/timeresp.py b/control/timeresp.py
@@ -1747,7 +1747,7 @@ def initial_response(
         Number of time steps to use in simulation if `T` is not provided as
         an array (autocomputed if not given); ignored if the system is
         discrete time.
-    
+
     params : dict, optional
         If system is a nonlinear I/O system, set parameter values.
 
