minor doc correction

Author: franckgaga

src/estimator/internal_model.jl

@@ -147,7 +147,7 @@ function init_internalmodel(As, Bs, Cs, Ds)
 end
 
 @doc raw"""
-    update_estimate!(estim::InternalModel, u, ym, d=Float64[])
+    update_estimate!(estim::InternalModel, u, ym, d=Float64[]) -> x̂d
 
 Update `estim.x̂` \ `x̂d` \ `x̂s` with current inputs `u`, measured outputs `ym` and dist. `d`.
 
@@ -175,7 +175,7 @@ function update_estimate!(estim::InternalModel, u, ym, d=Float64[])
 end
 
 @doc raw"""
-    initstate!(estim::InternalModel, u, ym, d=Float64[])
+    initstate!(estim::InternalModel, u, ym, d=Float64[]) -> x̂d
 
 Init `estim.x̂d` / `x̂s` states from current inputs `u`, meas. outputs `ym` and disturb. `d`.
 
@@ -192,7 +192,7 @@ function initstate!(estim::InternalModel, u, ym, d=Float64[])
 end
 
 @doc raw"""
-    evaloutput(estim::InternalModel, ym, d=Float64[])
+    evaloutput(estim::InternalModel, ym, d=Float64[]) -> ŷ
 
 Evaluate `InternalModel` outputs `ŷ` from `estim.x̂d` states and measured outputs `ym`.
 

src/plot_sim.jl

@@ -13,7 +13,7 @@ struct SimResult{O<:Union{SimModel, StateEstimator, PredictiveController}}
 end
 
 @doc raw"""
-    sim!(plant::SimModel, N::Int, u=plant.uop.+1, d=plant.dop; x0=zeros(plant.nx))
+    sim!(plant::SimModel, N::Int, u=plant.uop.+1, d=plant.dop; x0=zeros(plant.nx)) -> res
 
 Open-loop simulation of `plant` for `N` time steps, default to unit bump test on all inputs.
 
@@ -66,7 +66,7 @@ end
         u = estim.model.uop .+ 1,
         d = estim.model.dop;
         <keyword arguments>
-    )
+    ) -> res
 
 Closed-loop simulation of `estim` estimator for `N` time steps, default to input bumps.
 
@@ -120,7 +120,7 @@ end
         ry = mpc.estim.model.yop .+ 1, 
         d  = mpc.estim.model.dop; 
         <keyword arguments>
-    )
+    ) -> res
 
 Closed-loop simulation of `mpc` controller for `N` time steps, default to setpoint bumps.
 

src/predictive_control.jl

@@ -336,11 +336,11 @@ Set the estimate at `mpc.estim.x̂`.
 setstate!(mpc::PredictiveController, x̂) = (setstate!(mpc.estim, x̂); return mpc)
 
 @doc raw"""
-    initstate!(mpc::PredictiveController, u, ym, d=Float64[])
+    initstate!(mpc::PredictiveController, u, ym, d=Float64[]) -> x̂
 
 Init `mpc.ΔŨ` for warm-starting and the states of `mpc.estim` [`StateEstimator`](@ref).
 
-Before calling [`initstate!(::StateEstimator,_,_)`](@ref), it warm-starts ``\mathbf{ΔŨ}``:
+Before calling [`initstate!(mpc.estim, u, ym, d)`](@ref), it warm-starts ``\mathbf{ΔŨ}``:
 - If `model` is a [`LinModel`](@ref), the vector is filled with the analytical minimum ``J``
   of the unconstrained problem.
 - Else, the vector is filled with zeros.
@@ -352,7 +352,7 @@ end
 
 
 """
-    updatestate!(mpc::PredictiveController, u, ym, d=Float64[])
+    updatestate!(mpc::PredictiveController, u, ym, d=Float64[]) -> x̂
 
 Call [`updatestate!`](@ref) on `mpc.estim` [`StateEstimator`](@ref).
 """

src/sim_model.jl

@@ -99,7 +99,7 @@ function Base.show(io::IO, model::SimModel)
 end
 
 """
-    updatestate!(model::SimModel, u, d=Float64[])
+    updatestate!(model::SimModel, u, d=Float64[]) -> x
 
 Update `model.x` states with current inputs `u` and measured disturbances `d`.
 
@@ -118,7 +118,7 @@ function updatestate!(model::SimModel, u, d=Float64[])
 end
 
 """
-    evaloutput(model::SimModel, d=Float64[])
+    evaloutput(model::SimModel, d=Float64[]) -> y
 
 Evaluate `SimModel` outputs `y` from `model.x` states and measured disturbances `d`.
 

src/state_estim.jl

@@ -270,7 +270,7 @@ end
 
 
 @doc raw"""
-    initstate!(estim::StateEstimator, u, ym, d=Float64[])
+    initstate!(estim::StateEstimator, u, ym, d=Float64[]) -> x̂
 
 Init `estim.x̂` states from current inputs `u`, measured outputs `ym` and disturbances `d`.
 
@@ -329,7 +329,7 @@ init_deterstate(model::LinModel, _    , u, d) = steadystate(model, u, d)
 init_deterstate(model::SimModel, estim, _, _) = estim.x̂[1:model.nx]
 
 @doc raw"""
-    evaloutput(estim::StateEstimator, d=Float64[])
+    evaloutput(estim::StateEstimator, d=Float64[]) -> ŷ
 
 Evaluate `StateEstimator` outputs `ŷ` from `estim.x̂` states and disturbances `d`.
 
@@ -353,7 +353,7 @@ end
 
 
 @doc raw"""
-    updatestate!(estim::StateEstimator, u, ym, d=Float64[])
+    updatestate!(estim::StateEstimator, u, ym, d=Float64[]) -> x̂
 
 Update `estim.x̂` estimate with current inputs `u`, measured outputs `ym` and dist. `d`.