Python proof of concept for BCHOL.
Solves for x in Ax = b, using the Recursive Schur Linear Quadratic Regulator explained in the paper A Parallell Linear System Solver for Optimal Control by Brian E.Jackson. It requires A to be a positive semi-definite matrix to guarantee a good result.
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The following libraries (Numpy, Scipy) are included in the requirments.txt and can be downloaded with the following command
pip3 install -r requirements.txt
If you already have a defined LQR problem in a KKT form in a saved file .json/.csv you can look at solve_load.py
for an example.
If you just have an A matrix and a b vector look at solve_build.py
for an example.
Both files will return an xyz solution vector.
Author: Yana Botvinnik Contact: [email protected]