ParNMPC Version 1903-1

New Features in Version 1903-1:

Primal-dual interior-point method
Improved user interface
Better performance
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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.m and run.
Open Simu_Simulink_Setup.m and run.
Open Simu_Simulink.slx and 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.

mayataka/ParNMPC