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docs/make.jl

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"Systems" => "systems.md",
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"Barrier Functions" => "barriers.md",
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"Controllers" => "controllers.md",
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"Simulations" => "simulation.md",
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"Index" => "api.md",
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],
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)

docs/src/barriers.md

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## Implementation
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```@docs
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ControlBarrierFunction
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ControlBarrierFunction(h::Function, Σ::ControlAffineSystem, α::Function)
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ControlBarrierFunction(h::Function, Σ::ControlAffineSystem)
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```

docs/src/controllers.md

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## Quadratic Programming Safety Filters
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```@docs
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ExplicitSafetyFilter
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ExplicitSafetyFilter(cbf::ControlBarrierFunction, Σ::ControlAffineSystem, kd::Function)
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ExplicitSafetyFilter(cbf::ControlBarrierFunction, Σ::ControlAffineSystem)
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QPSafetyFilter
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QPSafetyFilter(cbf::ControlBarrierFunction, Σ::ControlAffineSystem, kd::Function)
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QPSafetyFilter(cbfs::Vector{ControlBarrierFunction}, Σ::ControlAffineSystem, kd::Function)
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TunableQPSafetyFilter
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```
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## Smooth Safety Filters
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```@docs
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SmoothSafetyFilter
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ISSfSmoothSafetyFilter
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```
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## Robust Safety Filters
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## Implementation

docs/src/index.md

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## Installation
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To download this package open the Julia REPL, enter the package manager (type `]` into the REPL) and run
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```julia
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using Pkg
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Pkg.add("https://github.com/maxhcohen/ControlBarrierFunctions.jl")
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add ControlBarrierFunctions
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```
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## Usage

docs/src/simulation.md

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# Simulations
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## Background
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We provide a shorthand function for running simulations of Control Affine Systems equipped with feedback controllers:
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```julia
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sol = simulate(Σ, k, x0, T)
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```
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where `Σ` is a `ControlAffineSystem`, `k` is a feedback controller of the form `k(x,t)` or `k(x)`, `x0` is the initial state, and `T` is the length of the simulation. This function simply calls a solver from `DifferentialEquations.jl` to simulate the closed-loop system and returns an ODE solution object.
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## Implementation
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```@docs
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simulate(Σ::ControlAffineSystem, x0, T::Float64)
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simulate(Σ::ControlAffineSystem, k::Function, x0, T::Float64)
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```

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