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correction nomenclature
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src/predictive_control.jl

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@@ -151,30 +151,30 @@ The controller minimizes the following objective function at each discrete time
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+ \mathbf{(R̂_u - U)}' \mathbf{L}_{H_p} \mathbf{(R̂_u - U)}
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+ C ϵ^2
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```
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in which the weight matrices are :
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in which the weight matrices are repeated ``H_p`` or ``H_c`` times :
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```math
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\begin{aligned}
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\mathbf{M}_{H_p} &= \text{diag}\mathbf{(M,M,...,M)} \\
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\mathbf{N}_{H_c} &= \text{diag}\mathbf{(N,N,...,N)} \\
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\mathbf{L}_{H_p} &= \text{diag}\mathbf{(L,L,...,L)}
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\end{aligned}
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```
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and following the nomeclature:
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| Var. | Description |
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| :------------------- | :------------------------------------------------- |
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| ``H_p`` | prediction horizon |
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| ``H_c`` | control horizon |
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| ``\mathbf{ΔU}`` | manipulated input increments over ``H_c`` |
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| ``\mathbf{Ŷ}`` | predicted outputs over ``H_p`` |
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| ``\mathbf{U}`` | manipulated inputs over ``H_p`` |
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| ``\mathbf{R̂_y}`` | predicted output setpoints over ``H_p`` |
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| ``\mathbf{R̂_u}`` | predicted manipulated input setpoints over ``H_p`` |
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| ``\mathbf{M}_{H_p}`` | output setpoint tracking weights |
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| ``\mathbf{N}_{H_c}`` | manipulated input increment weights |
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| ``\mathbf{L}_{H_p}`` | manipulated input setpoint tracking weights |
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| ``C`` | slack variable weight |
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| ``ϵ`` | slack variable for constraint softening |
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and with the following nomeclature:
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| Var. | Description |
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| :---------------- | :------------------------------------------------- |
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| ``H_p`` | prediction horizon |
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| ``H_c`` | control horizon |
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| ``\mathbf{ΔU}`` | manipulated input increments over ``H_c`` |
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| ``\mathbf{Ŷ}`` | predicted outputs over ``H_p`` |
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| ``\mathbf{U}`` | manipulated inputs over ``H_p`` |
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| ``\mathbf{R̂_y}`` | predicted output setpoints over ``H_p`` |
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| ``\mathbf{R̂_u}`` | predicted manipulated input setpoints over ``H_p`` |
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| ``\mathbf{M}`` | output setpoint tracking weights |
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| ``\mathbf{N}`` | manipulated input increment weights |
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| ``\mathbf{L}`` | manipulated input setpoint tracking weights |
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| ``C`` | slack variable weight |
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| ``ϵ`` | slack variable for constraint softening |
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The ``\mathbf{ΔU}`` vector includes the manipulated input increments ``\mathbf{Δu}(k+j) =
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\mathbf{u}(k+j) - \mathbf{u}(k+j-1)`` from ``j=0`` to ``H_c-1``, the ``\mathbf{Ŷ}`` vector,

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