/ParNMPC

A Parallel Optimization Toolkit for Nonlinear Model Predictive Control (NMPC)

Primary LanguageMATLAB

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

  1. Clone or download ParNMPC.
  2. 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)

  1. Select the Microsoft Visual C++ 2017 (C) compiler:
>> mex -setup
  1. Navigate to the Quadrotor/ folder.
>> cd  Quadrotor/
  1. Open NMPC_Problem_Formulation.m and run.

  2. Open Simu_Simulink_Setup.m and run.

  3. Open Simu_Simulink.slx and run.