ParNMPC Version 1903-1
New Features in Version 1903-1:
- Primal-dual interior-point method
- Improved user interface
- Better performance
- Line search
Introduction
Homepage: https://deng-haoyang.github.io/ParNMPC/
ParNMPC is a MATLAB real-time optimization toolkit for nonlinear model predictive control (NMPC).
The purpose of ParNMPC is to provide an easy-to-use environment for NMPC problem formulation, closed-loop simulation, and deployment.
With ParNMPC, you can define your own NMPC problem in a very easy way and ParNMPC will automatically generate self-contained C/C++ code for single- or multi-core CPUs.
ParNMPC is very fast even with only one core (the computation time is usually in the range of $\mu$s), and a high speedup can be achieved when parallel computing is enabled.
Highlights
- Symbolic problem representation
- Automatic parallel C/C++ code generation with OpenMP
- Fast rate of convergence (up to be superlinear)
- Highly parallelizable (capable of using at most N cores, N is the # of discretization steps)
- High speedup ratio
- MATLAB & Simulink
Installation
- Clone or download
ParNMPC. - Extract the downloaded file.
Requirements
- MATLAB 2016a or later
- MATLAB Coder
- MATLAB Optimization Toolbox
- MATLAB Parallel Computing Toolbox
- MATLAB Symbolic Math Toolbox
- Simulink Coder
- C/C++ compiler supporting parallel code generation
Getting Started (MATLAB 2018b)
- Select the Microsoft Visual C++ 2017 (C) compiler:
>> mex -setup- Navigate to the Quadrotor/ folder.
>> cd Quadrotor/-
Open
NMPC_Problem_Formulation.mand run. -
Open
Simu_Simulink_Setup.mand run. -
Open
Simu_Simulink.slxand run.
Citing ParNMPC
Citing the parallel algorithm:
@article{deng2019parallel,
title={A parallel Newton-type method for nonlinear model predictive control},
author={Deng, Haoyang and Ohtsuka, Toshiyuki},
journal={Automatica},
volume={109},
pages={108560},
year={2019}}
Citing the toolbox (conference version):
@inproceedings{deng2018parallel,
title={A parallel code generation toolkit for nonlinear model predictive control},
author={Deng, Haoyang and Ohtsuka, Toshiyuki},
booktitle={Proceedings of the 57th {IEEE} {C}onference on {D}ecision and {C}ontrol},
pages={4920--4926},
year={2018},
address={Miami, USA}}
License
ParNMPC is distributed under the BSD 2-Clause "Simplified" License.