FlightSims

FlightSims is a general-purpose numerical simulator by defining nested environments. This package can be used for any kind of numerical simulation with dynamical systems although it was supposed to be dedicated only for flight simulations.

Features

Compatibility

• It is compatible with OrdinaryDiffEq.jl. Supporting full compatibility with DifferentialEquations.jl is not on the road map for now. If you want more functionality, please feel free to report an issue!

Nested Environments and Zoo

• One can generate user-defined nested environments (or, dynamical systems) for complex flight simulation. Also, some predefined environments are provided for reusability (i.e., environment zoo). Take a look at src/environments.

Utilities

• Some utilities are also provided, for example, calculation of polynomial basis and 3D rotation. Take a look at src/utils.

APIs

Main APIs are provided in src/APIs.

Make an environment

• AbstractEnv: an abstract type for user-defined and predefined environments. All environment structures should be sub-type of AbstractEnv.
• State(env::AbstractEnv): return a function that produces structured states.
• dynamics!(env::AbstractEnv) and dynamics(env::AbstractEnv): return a function that maps in-place (recommended) and out-of-place dynamics (resp.), compatible with DifferentialEquations. User can extend these methods or simply define other methods.
• apply_inputs(func; kwargs...): It is borrowed from an MRAC example. By using this, user can easily apply various kind of inputs into the dynamical system (environment).

Simulation and data saving & loading

• To-do: Fill the following contents.
• sim: return prob::ODEProblem and sol::ODESolution.
• process: process prob and sol to get simulation data.
• save: save env, prob, sol, and optionally process, in a .jld2 file.
• load: load env, prob, sol, and optionally process, from a .jld2 file.

Usage

• For an example of infinite-horizon continuous-time linear quadratic regulator (LQR), take a look at test/lqr.jl.
• For an example of continuous-time value-iteration adaptive dynamic programming (CT-VI-ADP), take a look at main/continuous_time_vi_adp.jl.
  • T. Bian and Z.-P. Jiang, “Value Iteration, Adaptive Dynamic Programming, and Optimal Control of Nonlinear Systems,” in 2016 IEEE 55th Conference on Decision and Control (CDC), Las Vegas, NV, USA, Dec. 2016, pp. 3375–3380. doi: 10.1109/CDC.2016.7798777.
• To-do: add an example

Issues

• An issue has been reported; unknown crash between OrdinaryDiffEq and ComponentArrays. Will be resolved by this.