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