Peer-reviewedCC BYJournal of Open Source Software
OptimalControl.jl: a Julia package to model and solve optimal control problems with ODEs
Abstract
OptimalControl.jl (Caillau et al., 2026b) is a Julia (Bezanson et al., 2017) package for modeling and solving optimal control problems governed by ordinary differential equations (ODEs).As the core of the control-toolbox ecosystem, it provides a unified framework that supports both direct and indirect solution methods with applications spanning aerospace, medical imaging, epidemiology, and quantum control.
Related
- GridapGeosciences.jl: A Julia finite element package for partial differential equations on general manifolds
- A Stochastic Optimization Approach to Control-Affine Optimal Control Problems
- Robust preconditioners for finite element approximations of control-state constrained optimal control problems governed by elliptic equations
- Connection between MP and DPP for Mean-Field Stochastic Optimal Control Problems
- On quantitative sufficient second-order optimality conditions for elliptic optimal control problems
BibTeX
@article{caillau2026optimalcontroljl,
title = {{OptimalControl.jl: a Julia package to model and solve optimal control problems with ODEs}},
author = {Jean-Baptiste Caillau and Olivier Cots and Joseph Gergaud and Pierre Martinon and Sophia Sed},
journal = {Journal of Open Source Software},
year = {2026},
month = oct,
doi = {10.21105/joss.10630},
url = {https://hal.science/hal-05782187v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - OptimalControl.jl: a Julia package to model and solve optimal control problems with ODEs
AU - Jean-Baptiste Caillau
AU - Olivier Cots
AU - Joseph Gergaud
AU - Pierre Martinon
AU - Sophia Sed
PY - 2026
DA - 2026/10/03
JO - Journal of Open Source Software
DO - 10.21105/joss.10630
UR - https://hal.science/hal-05782187v1
AB - OptimalControl.jl (Caillau et al., 2026b) is a Julia (Bezanson et al., 2017) package for modeling and solving optimal control problems governed by ordinary differential equations (ODEs).As the core of the control-toolbox ecosystem, it provides a unified framework that supports both direct and indirect solution methods with applications spanning aerospace, medical imaging, epidemiology, and quantum control.
SN - 1942-3926
ER -