Merge pull request #309 from JuliaControl/minor_doc

doc: minor corrections

Author: franckgaga

docs/src/public/sim_model.md

@@ -14,7 +14,7 @@ method to manually modify them.
 !!! info
     The nomenclature in this page introduces the model manipulated input ``\mathbf{u}``,
     measured disturbances ``\mathbf{d}``, state ``\mathbf{x}`` and output ``\mathbf{y}``,
-    four vectors of `nu`, `nd`, `nx` and `ny` elements, respectively. The ``\mathbf{z}``
+    four vectors of `nu`, `nd`, `nx` and `ny` elements, respectively. The ``\mathbf{s}``
     vector combines the elements of ``\mathbf{u}`` and ``\mathbf{d}``.
 
 ## SimModel

ext/LinearMPCext.jl

@@ -212,7 +212,7 @@ end
 Convert a `ModelPredictiveControl.LinMPC` object to a `LinearMPC.MPC` object.
 
 The `LinearMPC` package needs to be installed and available in the activated Julia
-environment. The converted object can be used to generate lightweight C-code for embedded
+environment. The converted object can be used to generate lightweight C code for embedded
 applications using the `LinearMPC.codegen` function. Note that not all features of [`LinMPC`](@ref)
 are supported, including these restrictions:
 
@@ -221,7 +221,8 @@ are supported, including these restrictions:
 - the state estimator must be a [`SteadyKalmanFilter`](@ref) with `direct=true`.
 - only block-diagonal weights are allowed.
 - the constraint relaxation mechanism is different, so a 1-on-1 conversion of the soft 
-  constraints is impossible (use `Cwt=Inf` to disable relaxation).
+  constraints is impossible; expect differences in closed-loop behavior near the soft
+  bounds (or use `Cwt=Inf` to disable relaxation)
 
 But the package has also several exclusive functionalities, such as pre-stabilization,
 constrained explicit MPC, and binary manipulated inputs. See the [`LinearMPC.jl`](@extref LinearMPC)