diff --git a/doc/rcfs.pdf b/doc/rcfs.pdf
index c922fa01a21d8bdc2bf649653d4d017d6084269a..15c8064b7912ae9f73c9e51a71de4359b0b37128 100644
Binary files a/doc/rcfs.pdf and b/doc/rcfs.pdf differ
diff --git a/doc/rcfs.tex b/doc/rcfs.tex
index 8547bd7699cbf20beb8e2eb3eb23d5f59fa0898e..910979a8de39659566987b58e9847bcc85e4c1a8 100644
--- a/doc/rcfs.tex
+++ b/doc/rcfs.tex
@@ -1820,7 +1820,7 @@ For a tracking problem, we can see that the resulting optimal control policy tak
 	= \bm{K}_t \, (\bm{x}_t - \bm{\mu}_t) + \bm{u}^\text{ff}_t,
 	\label{eq:uLQTrecursive}
 \end{equation}
-characterized by a feedback gain matrix $\bm{K}_t$ extracted from $\bm{\tilde{K}}_t = \big[\bm{K}_t, \bm{k}_t\big]$, and a feedforward term $\bm{u}^\text{ff}_t = -\bm{k}_t - \bm{K}_t \bm{\mu}_t$ depending on $\bm{\mu}_t$.
+characterized by a feedback gain matrix $\bm{K}_t$ extracted from $\bm{\tilde{K}}_t = \big[\bm{K}_t, \bm{k}_t\big]$, and a feedforward term $\bm{u}^\text{ff}_t = \bm{k}_t - \bm{K}_t \bm{\mu}_t$ depending on $\bm{\mu}_t$.
 %K = Ka(:,1:model0.nbVar);
 %uff = -Ka(:,end) - K * model0.Mu(:,qList(t));
 %u = K * (model0.Mu(:,qList(t)) - x(1:end-1)) + uff; %Acceleration command with FB and FF terms computed explicitly from Ka