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docs: clarify lqe and dlqe error covariance wording #1219

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docs: clarify lqe and dlqe error covariance wording #1219

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12 changes: 6 additions & 6 deletions control/stochsys.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,9 +54,9 @@ def lqe(*args, **kwargs):

.. math:: dx_e/dt = A x_e + B u + L(y - C x_e - D u)

produces a state estimate x_e that minimizes the expected squared error
using the sensor measurements y. The noise cross-correlation `NN` is
set to zero when omitted.
produces a state estimate x_e that minimizes the mean squared
estimation error x - x_e using the sensor measurements y. The noise
cross-correlation `NN` is set to zero when omitted.

The function can be called with either 3, 4, 5, or 6 arguments:

Expand Down Expand Up @@ -204,9 +204,9 @@ def dlqe(*args, **kwargs):

.. math:: x_e[n+1] = A x_e[n] + B u[n] + L(y[n] - C x_e[n] - D u[n])

produces a state estimate x_e[n] that minimizes the expected squared
error using the sensor measurements y. The noise cross-correlation `NN`
is set to zero when omitted.
produces a state estimate x_e[n] that minimizes the mean squared
estimation error x[n] - x_e[n] using the sensor measurements y. The
noise cross-correlation `NN` is set to zero when omitted.

Parameters
----------
Expand Down