minor doc correction

Author: franckgaga

src/estimator/kalman.jl

@@ -24,8 +24,9 @@ struct SteadyKalmanFilter <: StateEstimator
     K̂::Matrix{Float64}
     function SteadyKalmanFilter(model, i_ym, nint_u, nint_ym, Q̂, R̂)
         nym, nyu = validate_ym(model, i_ym)
-        As, Cs_u, Cs_y, nxs, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
-        nx̂ = model.nx + nxs
+        As, Cs_u, Cs_y, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
+        nxs = size(As, 1)
+        nx̂  = model.nx + nxs
         Â, B̂u, Ĉ, B̂d, D̂d = augment_model(model, As, Cs_u, Cs_y)
         validate_kfcov(nym, nx̂, Q̂, R̂)
         K̂ = try
@@ -207,8 +208,9 @@ struct KalmanFilter <: StateEstimator
     M̂::Matrix{Float64}
     function KalmanFilter(model, i_ym, nint_u, nint_ym, P̂0, Q̂, R̂)
         nym, nyu = validate_ym(model, i_ym)
-        As, Cs_u, Cs_y, nxs, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
-        nx̂ = model.nx + nxs
+        As, Cs_u, Cs_y, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
+        nxs = size(As, 1)
+        nx̂  = model.nx + nxs
         Â, B̂u, Ĉ, B̂d, D̂d = augment_model(model, As, Cs_u, Cs_y)
         validate_kfcov(nym, nx̂, Q̂, R̂, P̂0)
         Ĉm, D̂dm = Ĉ[i_ym, :], D̂d[i_ym, :] # measured outputs ym only
@@ -355,8 +357,9 @@ struct UnscentedKalmanFilter{M<:SimModel} <: StateEstimator
         model::M, i_ym, nint_u, nint_ym, P̂0, Q̂, R̂, α, β, κ
     ) where {M<:SimModel}
         nym, nyu = validate_ym(model, i_ym)
-        As, Cs_u, Cs_y, nxs, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
-        nx̂ = model.nx + nxs
+        As, Cs_u, Cs_y, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
+        nxs = size(As, 1)
+        nx̂  = model.nx + nxs
         Â, B̂u, Ĉ, B̂d, D̂d = augment_model(model, As, Cs_u, Cs_y)
         validate_kfcov(nym, nx̂, Q̂, R̂, P̂0)
         nσ, γ, m̂, Ŝ = init_ukf(nx̂, α, β, κ)
@@ -594,8 +597,9 @@ struct ExtendedKalmanFilter{M<:SimModel} <: StateEstimator
         model, i_ym, nint_u, nint_ym, P̂0, Q̂, R̂
     ) where {M<:SimModel}
         nym, nyu = validate_ym(model, i_ym)
-        As, Cs_u, Cs_y, nxs, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
-        nx̂ = model.nx + nxs
+        As, Cs_u, Cs_y, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
+        nxs = size(As, 1)
+        nx̂  = model.nx + nxs
         Â, B̂u, Ĉ, B̂d, D̂d = augment_model(model, As, Cs_u, Cs_y)
         validate_kfcov(nym, nx̂, Q̂, R̂, P̂0)
         lastu0 = zeros(model.nu)

src/estimator/luenberger.jl

@@ -22,8 +22,9 @@ struct Luenberger <: StateEstimator
     K̂::Matrix{Float64}
     function Luenberger(model, i_ym, nint_u, nint_ym, p̂)
         nym, nyu = validate_ym(model, i_ym)
-        As, Cs_u, Cs_y, nxs, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
-        nx̂ = model.nx + nxs
+        As, Cs_u, Cs_y, nint_u, nint_ym = init_estimstoch(model, i_ym, nint_u, nint_ym)
+        nxs = size(As, 1)
+        nx̂  = model.nx + nxs
         Â, B̂u, Ĉ, B̂d, D̂d = augment_model(model, As, Cs_u, Cs_y)
         K̂ = try
             place(Â, Ĉ, p̂, :o)[:, i_ym]

src/state_estim.jl

@@ -79,13 +79,13 @@ manipulated input and measured outputs. The function returns the state-space mat
 `Cs_u` and `Cs_y` of the stochastic model:
 ```math
 \begin{aligned}
-\mathbf{x_s}(k+1)    &= \mathbf{A_s x_s}(k) + \mathbf{B_s e}(k) \\
-\mathbf{y_s_{u}}(k)  &= \mathbf{C_s_{u}  x_s}(k) \\
-\mathbf{y_s_{ym}}(k) &= \mathbf{C_s_{ym} x_s}(k) \\
+\mathbf{x_{s}}(k+1)     &= \mathbf{A_s x_s}(k) + \mathbf{B_s e}(k) \\
+\mathbf{y_{s_{u}}}(k)   &= \mathbf{C_{s_{u}}  x_s}(k) \\
+\mathbf{y_{s_{ym}}}(k)  &= \mathbf{C_{s_{ym}} x_s}(k) 
 \end{aligned}
 ```
 where ``\mathbf{e}(k)`` is an unknown zero mean white noise and ``\mathbf{A_s} = 
-\mathrm{diag}(\mathbf{A_s_{u}, A_s_{ym}})``. The estimations does not use ``\mathbf{B_s}``,
+\mathrm{diag}(\mathbf{A_{s_{u}}, A_{s_{ym}}})``. The estimations does not use ``\mathbf{B_s}``,
 it is thus ignored. The function [`init_integrators`](@ref) builds the state-space matrices.
 """
 function init_estimstoch(model, i_ym, nint_u::IntVectorOrInt, nint_ym::IntVectorOrInt)
@@ -98,8 +98,7 @@ function init_estimstoch(model, i_ym, nint_u::IntVectorOrInt, nint_ym::IntVector
     As   = [As_u zeros(nxs_u, nxs_y); zeros(nxs_y, nxs_u) As_y]
     Cs_u = [Cs_u zeros(nu, nxs_y)]
     Cs_y = [zeros(ny, nxs_u) Cs_y]
-    nxs = nxs_u + nxs_y
-    return As, Cs_u, Cs_y, nxs, nint_u, nint_ym
+    return As, Cs_u, Cs_y, nint_u, nint_ym
 end
 
 "Validate the specified measured output indices `i_ym`."