2021-code-convergence-properties-of-fast-quasi-lpv-model-predictive-control

Code for the paper "Convergence Properties of Fast quasi-LPV Model Predictive Control" by C. Hespe and H. Werner

https://github.com/tuhh-ics/2021-code-convergence-properties-of-fast-quasi-lpv-model-predictive-control

Science Score: 67.0%

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  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 6 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (11.2%) to scientific vocabulary

Keywords

model-predictive-control
Last synced: 6 months ago · JSON representation ·

Repository

Code for the paper "Convergence Properties of Fast quasi-LPV Model Predictive Control" by C. Hespe and H. Werner

Basic Info
  • Host: GitHub
  • Owner: TUHH-ICS
  • License: gpl-3.0
  • Language: MATLAB
  • Default Branch: master
  • Homepage: https://www.tuhh.de/ics/
  • Size: 50.8 KB
Statistics
  • Stars: 6
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
  • Releases: 2
Topics
model-predictive-control
Created almost 5 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.md

Convergence Properties of Fast quasi-LPV Model Predictive Control

DOI

General

This repository contains the simulation code to reproduce the tables and figures presented in

C. Hespe and H. Werner, "Convergence Properties of Fast quasi-LPV Model Predictive Control," 60th Conference on Decision and Control. Austin, TX, USA, 2021, doi: 10.1109/CDC45484.2021.9683612.

The code has two main entry points, the scripts benchmark_adip.m and benchmark_unicycle.m, both in the root directory of this repository. They will produce among others the material presented in the paper.

Prerequisites

To run the simulation files, some additional packages need to be installed first.

  1. Install acados, e.g. according to this guide
  2. Install CasADi into the external directory of acados, as described on the acados interface page
  3. Create the environment variable ACADOS_INSTALL_DIR pointing to the main acados directory

The simulation code in this repository was tested in the following environment:

  • Windows 10 Version 21H1
  • Matlab 2021a
  • acados 0.1.6
  • CasADi 3.5.5

In the default configuration, you will also need the Matlab Coder. It is used to generate C code for the qLMPC solvers. If you do not have access to Matlab Coder and want to run the simulation nonetheless, you can disable code generation in the main simulation scripts by setting generate_mex = false.

Owner

  • Name: Institute of Control Systems - TUHH
  • Login: TUHH-ICS
  • Kind: organization
  • Email: ics@tuhh.de
  • Location: Hamburg, Germany

Citation (CITATION.cff)

cff-version: 1.2.0
title: Convergence Properties of Fast quasi-LPV Model Predictive Control
message: If you use this software, please cite it using the metadata from this file.
type: software
authors:
  - given-names: Christian
    family-names: Hespe
    affiliation: Hamburg University of Technology, Institute of Control Systems
    orcid: 'https://orcid.org/0000-0001-5772-9044'
  - given-names: Herbert
    family-names: Werner
    affiliation: Hamburg University of Technology, Institute of Control Systems
    orcid: 'https://orcid.org/0000-0003-3456-5539'
identifiers:
  - type: doi
    value: 10.1109/CDC45484.2021.9683612
    description: DOI of the accompanying paper
  - type: doi
    value: 10.5281/zenodo.4633758
    description: DOI of the Zenodo archive
repository-code: https://github.com/TUHH-ICS/2021-code-convergence-properties-of-fast-quasi-lpv-model-predictive-control
repository: https://arxiv.org/abs/2309.07375
keywords:
  - model predictive control
  - optimization
  - linear parameter-varying systems
license: GPL-3.0

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