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CITATION.cff

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given-names: "Fredrik"
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title: "ModelPredictiveControl.jl: advanced process control made easy in Julia"
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year: 2024
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doi: "10.1007/978-3-030-68928-5"
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doi: "10.48550/arXiv.2411.09764"
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url: "https://arxiv.org/abs/2411.09764"

docs/src/manual/installation.md

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using Pkg; Pkg.generate("MPCproject"); Pkg.activate("."); Pkg.add("ModelPredictiveControl")
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```
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Note that that the construction of linear models typically requires `ss` or `tf` functions,
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Note that the construction of linear models typically requires `ss` or `tf` functions,
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it is thus advised to load the package with:
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```julia

src/controller/explicitmpc.jl

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constraints but the computational costs are extremely low (array division), therefore
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suitable for applications that require small sample times. The keyword arguments are
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identical to [`LinMPC`](@ref), except for `Cwt`, `transcription` and `optim`, which are not
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supported. This controller uses a [`SingleShooting`](@ref) transcription method.
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supported. It uses a [`SingleShooting`](@ref) transcription method and is allocation-free.
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This method uses the default state estimator, a [`SteadyKalmanFilter`](@ref) with default
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arguments. This controller is allocation-free.
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arguments.
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# Examples
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```jldoctest

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