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ModelPredictiveControl.jl

An open source model predictive control package for Julia.

The package depends on ControlSystemsBase.jl for the linear systems, JuMP.jl for the optimization and DifferentiationInterface.jl for the derivatives.

The objective is to provide a simple, clear and modular framework to quickly design model predictive controllers (MPCs) in Julia, while preserving the flexibility for advanced real-time optimization. Modern MPCs based on closed-loop state estimators are the main focus of the package, but classical approaches that rely on internal models are also possible. The JuMP and DifferentiationInterface dependencies allows the user to test different optimizers and automatic differentiation (AD) backends easily if the performances of the default settings are not satisfactory. Linear MPC controllers can be exported to lightweight and standalone C code via the LinearMPC package extension.

The documentation is divided in two parts:

  • [Manual](@ref man_lin) — This section includes step-by-step guides to design predictive controllers on multiple case studies.
  • [Functions](@ref func_sim_model) — Documentation of methods and types exported by the package. The "Internals" section provides implementation details of functions that are not exported.

Manual

Depth = 2
Pages = [
    "manual/installation.md",
    "manual/linmpc.md",
    "manual/nonlinmpc.md",
    "manual/mtk.md"
]

Functions: Public

Depth = 2
Pages = [
    "public/sim_model.md",
    "public/state_estim.md",
    "public/predictive_control.md",
    "public/generic_func.md",
    "public/plot_sim.md",
]

Functions: Internals

Depth = 1
Pages = [
    "internals/sim_model.md",
    "internals/state_estim.md",
    "internals/predictive_control.md",
]