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Implementation of SCvx, linear MPC and LQR for trajectory generation and tracking

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This library implements various optimal control algorithms that are particularly suited for aerospace applications.

Guidance and Control Algorithms

  • Efficient Successive Convexification, a real-time guidance algorithm for optimal trajectory planning of constrained dynamical systems
  • Generic linear receding-horizon SOCP MPC algorithm
  • Linear Quadratic Regulator

Features

  • JIT derivative code generation with CppAD/CppADCodegen
  • Intuitive interface to implement custom models
  • Rapid iteration with parameters files

Current Models

  • 2D Rocket Model
  • Rocket Landing Model with Quaternion
  • Rocket Landing Model with Euler Angles

Dependencies

  • C++17
  • Eigen
  • Boost (odeint and ptree)
  • fmt (included as submodule)
  • CppAD/CppADCodegen (included as submodule)
  • Epigraph (included as submodule)

Instructions

Install

git clone --recurse-submodules https://github.com/EmbersArc/SCpp.git
cd SCpp
mkdir build
cd build
cmake ..
make

Run

Available executables are:

  • LQR_sim to simulate a trajectory with the classic MPC controller

  • MPC_sim to simulate a trajectory with the classic MPC controller

  • SC_oneshot to calculate one trajectory with Successive Convexification

  • SC_sim to simulate a trajectory with Successive Convexification

Calculated trajectories are written to the output/<modelname> directory.

Create a Custom Model

See existing models in the socp_models folder for some examples.

Papers

Examples

(click on videos for higher quality versions)

Rocket Trajectory Model with Free-Final-Time

SpaceX Starship Landing Trajectory

2D Rocket Landing Problem

feed-forward input tested in a box2d physics simulation

Cartpole

Contributing

I'm looking forward to contributions, both problem formulations and improvements to the core library.

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