docs corrections

Author: baggepinnen

docs/src/lqg_disturbance.md

@@ -98,4 +98,4 @@ f2 = gangoffourplot(prob, w, lab = "", legend = :bottomright)
 plot(f1, f2, titlefontsize=10)
 ```
 
-We see that we now have a slightly larger disturbance response than before, but in exchange, we lowered the peak sensitivity and complimentary sensitivity from (1.5, 1.31) to (1.25, 1.11), a more robust design. We also reduced the amplification of measurement noise ($CS = C/(1+PC)$). To be really happy with the design, we should probably add high-frequency roll-off as well.
+We see that we now have a slightly larger disturbance response than before, but in exchange, we lowered the peak sensitivity and complimentary sensitivity from (1.51, 1.25) to (1.31, 1.11), a more robust design. We also reduced the amplification of measurement noise ($CS = C/(1+PC)$). To be really happy with the design, we should probably add high-frequency roll-off as well.

docs/src/uncertainty.md

@@ -284,7 +284,7 @@ This time, we keep the same output dimension, but the state dimension is reduced
 Pred.nx
 ```
 
-Note, `Pred` here represents the uncertain model with a single deterministic model of order `P.nx`, while the original uncertain model `P` was represented by 2000 internal models of state dimension 2.
+Note, `Pred` here represents the uncertain model with a single deterministic model of order `Pred.nx`, while the original uncertain model `P` was represented by 2000 internal models of state dimension 2.
 
 ## Using the $M\Delta$ framework
 The examples above never bothered with things like the "structured singular value", $\mu$ or linear-fractional transforms. We do, however, provide some elementary support for this modeling framework.