Skip to content

Latest commit

 

History

History
25 lines (19 loc) · 1.56 KB

README.md

File metadata and controls

25 lines (19 loc) · 1.56 KB

README (dt-qp-project)

This project solves linear-quadratic dynamic optimization (LQDO) problems using direct transcription (DT) and quadratic programming (QP)

readme_image.svg

Citation

Please cite the following two items if you use the DT QP Project:

  • DR Herber. Advances in Combined Architecture, Plant, and Control Design. PhD Dissertation, University of Illinois at Urbana-Champaign, Urbana, IL, USA, Dec. 2017. [bibtex] [pdf]
    • Discusses the theory behind this project and contains a number of examples comparing the different methods.
  • DR Herber, YH Lee, JT Allison. DT QP Project, GitHub. url: https://github.com/danielrherber/dt-qp-project

General Information

This is a limited implementation of the DTQP in python to solve strictly linear-quadratic dynamic optimizations problems on simple equi-distant mesh. Unlike DTQP, DTQPy has only the composite trapezoidal (CTR) method implemented for transcribing the objective function, and the dynamic constraints. Additionally, no mesh-refinement feature has been implemented.

Contributors