S
Sina Ober-Blöbaum
Researcher at University of Paderborn
Publications - 123
Citations - 1795
Sina Ober-Blöbaum is an academic researcher from University of Paderborn. The author has contributed to research in topics: Optimal control & Variational integrator. The author has an hindex of 20, co-authored 117 publications receiving 1525 citations. Previous affiliations of Sina Ober-Blöbaum include University of Oxford & California Institute of Technology.
Papers
More filters
Journal ArticleDOI
Discrete mechanics and optimal control: an analysis ∗
TL;DR: The DMOC (Discrete Mechanics and Optimal Control) approach is equivalent to a finite difference discretization of Hamilton's equations by a symplectic partitioned Runge-Kutta scheme and this fact is employed in order to give a proof of convergence.
Journal ArticleDOI
Discrete mechanics and optimal control
TL;DR: In this article, a new approach to the solution of optimal control problems for mechanical systems is proposed, based on a direct discretization of the Lagrange-d'Alembert principle for the system (as opposed to using collocation or multiple shooting to enforce the equations of motion as constraints).
Journal ArticleDOI
Discrete mechanics and optimal control for constrained systems
TL;DR: In this paper, the Lagrange-d'Alembert principle is applied to a structure-preserving scheme for the optimal control of a multibody system subject to holonomic constraints.
Journal ArticleDOI
Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modelling
TL;DR: For the first time, this paper quantifies the annual benefits of grid-connected batteries including realistic physical dynamics and nonlinear electrochemical degradation and shows that the revenue can be increased substantially while degradation can be reduced by using more realistic models.
Proceedings ArticleDOI
Optimal trajectory generation for a glider in time-varying 2D ocean flows B-spline model
TL;DR: The results show that the 2D and time-varying B-spline ocean model not only can make the whole trajectory generating process much easier, but also the glider can reach the same destination in a comparable time and with much less energy than it does with the previous 2D ocean current model.