This is HPIPM, a high-performance interior-point method solver for dense, optimal control- and tree-structured convex quadratic programs. It provides efficient implementations of dense and structure-exploiting algorithms to solve small to medium scale problems arising in model predictive control and embedded optimization in general and it relies on the high-performance linear algebra package BLASFEO.

Getting Started:

The best way to get started with HPIPM is to check out the examples in /hpipm/examples/c/ and /hpipm/examples/python/. In order to run the C example, follow the steps below:

1. clone BLASFEO on your machine: 'git clone https://github.com/giaf/blasfeo.git'
2. from the BLASFEO root folder, run 'make static_library & sudo make install_static'
3. from the HPIPM root folder, run 'make static_library & make examples'
4. cd to /hpipm/examples/c/ and run getting_started.out to solve a simple OCP-structured QP.

If you would like to try out the Python interface, you will need to proceed as follows:

1. clone BLASFEO on your machine: 'git clone https://github.com/giaf/blasfeo.git'
2. from the BLASFEO root folder, run 'make shared_library & sudo make install_shared'
3. from the HPIPM root folder, run 'make shared_library & sudo make install_shared'
4. make sure that the location of the installed shared libraries is known to the system by running 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/blasfeo/lib:/opt/hpipm/lib'. If you would like to avoid running this command whenever opening a new shell. You can add the commands above to your .bashrc.
5. cd to /hpipm/interfaces/python/hpipm_python and run 'pip3 install .'
6. cd to /hpipm/examples/python and run 'python3 getting_started.py' to solve a simple OCP-structured QP.

References:

• G. Frison, H.H. B. Sørensen, B. Dammann, and J.B. Jørgensen. High-performance small-scale solvers for linear model predictive control. In IEEE European Control Conference, pages 128–133. IEEE, 2014 - https://ieeexplore.ieee.org/document/6981589/

• BLASFEO: Basic Linear Algebra Subroutines For Embedded Optimization G. Frison, D. Kouzoupis, T. Sartor, A. Zanelli, M. Diehl ACM Transactions on Mathematical Software (TOMS) (2018) - https://arxiv.org/abs/1704.02457

• https://github.com/giaf/blasfeo

Notes:

• HPIPM is released under the GPL+CE (Gnu General Public License version 3.0 with Classpath Exception). This license has been chosen to avoid the issues that the LGPL license implies in case of static linking. Unformally speaking, the GPL+CE license allows the BLASFEO library to be linked to both statically and dynamically to produce an executable, and the resulting executable can be released under terms of your choice. Please refer to the LICENSE.txt file for the legally binding statement of the license.