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src/predictive_control.jl

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@@ -780,11 +780,10 @@ The linear model predictions are evaluated by :
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&= \mathbf{E ΔU} + \mathbf{F}
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\end{aligned}
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```
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where predicted outputs ``\mathbf{Ŷ}``, stochastic outputs ``\mathbf{Ŷ_s}``, and measured
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disturbances ``\mathbf{D̂}`` are from ``k + 1`` to ``k + H_p``. Input increments
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``\mathbf{ΔU}`` are from ``k`` to ``k + H_c - 1``. The vector ``\mathbf{x̂}_{k-1}(k)`` is the
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state estimated at the last control period. The method also computes similar matrices but
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for the predicted terminal states at ``k+H_p``:
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where predicted outputs ``\mathbf{Ŷ}`` and measured disturbances ``\mathbf{D̂}`` are from ``k
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+ 1`` to ``k + H_p``. Input increments ``\mathbf{ΔU}`` are from ``k`` to ``k + H_c - 1``.
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The vector ``\mathbf{x̂}_{k-1}(k)`` is the state estimated at the last control period. The
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method also computes similar matrices but for the predicted terminal states at ``k+H_p``:
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```math
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\begin{aligned}
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\mathbf{x̂}_{k-1}(k+H_p)

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