From 516ba2eb754185aad78da2f88b6c0de3d8403479 Mon Sep 17 00:00:00 2001 From: marko1olo Date: Thu, 13 Aug 2026 23:28:24 +0400 Subject: [PATCH] docs: clarify lqe and dlqe error covariance wording --- control/stochsys.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/control/stochsys.py b/control/stochsys.py index 756d83e13..22e2f738b 100644 --- a/control/stochsys.py +++ b/control/stochsys.py @@ -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: @@ -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 ----------