Zobrazeno 1 - 10
of 14
pro vyhledávání: '"George I. Boutselis"'
Publikováno v:
Entropy, Vol 23, Iss 8, p 941 (2021)
Stochastic spatio-temporal processes are prevalent across domains ranging from the modeling of plasma, turbulence in fluids to the wave function of quantum systems. This letter studies a measure-theoretic description of such systems by describing the
Externí odkaz:
https://doaj.org/article/ec4a155c82c94e7886d89907191b0c3d
Publikováno v:
IEEE Transactions on Automatic Control. 66:4636-4651
We develop a discrete-time optimal control framework for systems evolving on Lie groups. Our article generalizes the original differential dynamic programming method, by employing a coordinate-free, Lie-theoretic approach for its derivation. A key el
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c9d270ba4bbe10427cc6e369716a80ad
https://doi.org/10.1109/tac.2020.3034206
https://doi.org/10.1109/tac.2020.3034206
Publikováno v:
Entropy, Vol 23, Iss 941, p 941 (2021)
Entropy
Volume 23
Issue 8
Entropy
Volume 23
Issue 8
Stochastic spatio-temporal processes are prevalent across domains ranging from the modeling of plasma, turbulence in fluids to the wave function of quantum systems. This letter studies a measure-theoretic description of such systems by describing the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35f3b3fa9c3dd81cabc144b743e6a72d
https://www.mdpi.com/1099-4300/23/8/941
https://www.mdpi.com/1099-4300/23/8/941
Publikováno v:
SIAM Journal on Scientific Computing. 41:A2065-A2087
In this paper we develop a novel optimal control framework for uncertain mechanical systems. Our work extends differential dynamic programming and handles uncertainty through generalized polynomial...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a762f19bc6696efa1b32738ac1f0626
https://doi.org/10.1137/17m116272x
https://doi.org/10.1137/17m116272x
Publikováno v:
Robotics: Science and Systems
There is a rising interest in Spatio-temporal systems described by Partial Differential Equations (PDEs) among the control community. Not only are these systems challenging to control, but the sizing and placement of their actuation is an NP-hard pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c1c44661919f16a681306c83ee04638
https://doi.org/10.15607/rss.2020.xvi.049
https://doi.org/10.15607/rss.2020.xvi.049
Publikováno v:
ICRA
Differential Dynamic Programming (DDP) has become a well established method for unconstrained trajectory optimization. Despite its several applications in robotics and controls however, a widely successful constrained version of the algorithm has yet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51ffa8da8ad4c730a772eb91485dc938
http://arxiv.org/abs/2005.00985
http://arxiv.org/abs/2005.00985
Publikováno v:
ICRA
We propose a sampling-based trajectory optimization methodology for constrained problems. We extend recent works on stochastic search to deal with box control constraints, as well as nonlinear state constraints for discrete dynamical systems. Regardi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc1e3bad1d6670a5b78a03ae9c732b67
Publikováno v:
CDC
Path Integral control theory yields a sampling-based methodology for solving stochastic optimal control problems. Motivated by its computational efficiency, we extend this framework to account for systems evolving on Lie groups. Our derivation relies
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de6126c7a4b5e14942f51d2ff580d510
https://doi.org/10.1109/cdc.2018.8619818
https://doi.org/10.1109/cdc.2018.8619818
Publikováno v:
CDC
In this paper we investigate whether the linearly solvable stochastic optimal control framework generalizes to the case of stochastic differential equations in infinite dimensional spaces. In particular, we show that the connection between the relati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b753f3e1fd9eb7b586d78f5d22d4c9c
https://doi.org/10.1109/cdc.2018.8618948
https://doi.org/10.1109/cdc.2018.8618948
Publikováno v:
CDC
We propose a novel methodology for stochastic trajectory optimization which is based on merging the theory of spectral expansions with Differential Dynamic Programming. Specifically, we employ polynomial chaos expansions to handle parametric uncertai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b835df5f336cf6922296e2cf3d379835
https://doi.org/10.1109/cdc.2016.7798560
https://doi.org/10.1109/cdc.2016.7798560