NonLinModel: default_nintreturns 0 with nint_u

Author: franckgaga

docs/src/manual/linmpc.md

@@ -54,13 +54,13 @@ model = setop!(LinModel(sys, Ts), uop=[20, 20], yop=[50, 30])
 ```
 
 The `model` object will be used for two purposes : to construct our controller, and as a
-plant simulator to test the design.
+plant simulator to test the design. Its sampling time is 2 s thus the control period will be
+2 s as well.
 
 ## Linear Model Predictive Controller
 
 A linear model predictive controller (MPC) will control both the water level ``y_L`` and
-temperature ``y_T`` in the tank, at a sampling time of 2 s. The tank level should also never
-fall below 45:
+temperature ``y_T`` in the tank. The tank level should also never fall below 45:
 
 ```math
 y_L ≥ 45

src/controller/linmpc.jl

@@ -108,7 +108,7 @@ arguments.
 - `optim=JuMP.Model(OSQP.MathOptInterfaceOSQP.Optimizer)` : quadratic optimizer used in
   the predictive controller, provided as a [`JuMP.Model`](https://jump.dev/JuMP.jl/stable/api/JuMP/#JuMP.Model)
   (default to [`OSQP.jl`](https://osqp.org/docs/parsers/jump.html) optimizer).
-- additionnal keyword arguments are passed to [`SteadyKalmanFilter`](@ref) constructor.
+- additional keyword arguments are passed to [`SteadyKalmanFilter`](@ref) constructor.
 
 # Examples
 ```jldoctest

src/state_estim.jl

@@ -250,10 +250,14 @@ end
     default_nint(model::SimModel, i_ym=1:model.ny, nint_u=0)
 
 One integrator on each measured output by default if `model` is not a  [`LinModel`](@ref).
+
+If the integrator quantity per manipulated input `nint_u ≠ 0`, the method returns zero
+integrator on each measured output.
 """
 function default_nint(model::SimModel, i_ym=1:model.ny, nint_u=0)
     validate_ym(model, i_ym)
-    return fill(1, length(i_ym))
+    nint_ym = iszero(nint_u) ? fill(1, length(i_ym)) : fill(0, length(i_ym))
+    return nint_ym
 end
 
 @doc raw"""