Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Soumya Vasisht"'
Publikováno v:
IEEE Open Journal of Control Systems, Vol 1, Pp 100-112 (2022)
In this paper, we provide sufficient conditions for dissipativity and local asymptotic stability of discrete-time dynamical systems parametrized by deep neural networks. We leverage the representation of neural networks as pointwise affine maps, thus
Externí odkaz:
https://doaj.org/article/cd7b89bb71994d95b1ef04382540f209
Estimating Driver Response Rates to Variable Message Signage at Seattle-Tacoma International Airport
Publikováno v:
Findings (2022)
We apply Bayesian Linear Regression to estimate the response rate of drivers to variable message signs at Seattle-Tacoma International Airport, or SEA. Our approach uses vehicle speed and flow data measured at the entrances of the arrival and departu
Externí odkaz:
https://doaj.org/article/0230db25a7794347bbca272f8dd70244
Publikováno v:
IFAC-PapersOnLine. 56:228-233
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5e85479e328b000daeaf5dd7cbb0fe3
https://doi.org/10.1016/j.ifacol.2023.02.039
https://doi.org/10.1016/j.ifacol.2023.02.039
Publikováno v:
2022 Resilience Week (RWS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3f9a26e067ba8a603c0edb9c70af718
https://doi.org/10.1109/rws55399.2022.9984030
https://doi.org/10.1109/rws55399.2022.9984030
Publikováno v:
IFAC-PapersOnLine. 54:14-19
We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a914d2af2c2f5a85ebb3a6aaf6cb825d
https://doi.org/10.1016/j.ifacol.2021.08.518
https://doi.org/10.1016/j.ifacol.2021.08.518
Autor:
Soumya Vasisht, Aowabin Rahman, Thiagarajan Ramachandran, Arnab Bhattacharya, Veronica Adetola
Publikováno v:
2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bfdfff0a0c4018d807553f22b8f68de8
https://doi.org/10.1109/iccps54341.2022.00040
https://doi.org/10.1109/iccps54341.2022.00040
Autor:
Soumya Vasisht, Mehran Mesbahi
Publikováno v:
Journal of Guidance, Control, and Dynamics. 43:1540-1549
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9c315492b88eea502932228653bb3f3
https://doi.org/10.2514/1.g004601
https://doi.org/10.2514/1.g004601
Autor:
Draguna Vrabie, Himanshu Sharma, Sen Huang, Veronica Adetola, Arnab Bhattacharya, Soumya Vasisht
Publikováno v:
ACC
Sequential approaches to system and control design produce sub-optimal solutions due to unidirectional coupling between the system and control variables, i.e., the system design prescribes the control approach but not vice versa. A critical challenge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b8d6c20d9e54f6173216a3f46d751ef
https://doi.org/10.23919/acc50511.2021.9483129
https://doi.org/10.23919/acc50511.2021.9483129
Publikováno v:
ACC
Neural network modules conditioned by known priors can be effectively trained and combined to represent systems with nonlinear dynamics. This work explores a novel formulation for data-efficient learning of deep control-oriented nonlinear dynamical m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04704fd8b73fb58578e1cfa465d13c52
In this paper, we provide sufficient conditions for dissipativity and local asymptotic stability of discrete-time dynamical systems parametrized by deep neural networks. We leverage the representation of neural networks as pointwise affine maps, thus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::899c810ffd4cf8946da35441b290a2ef
http://arxiv.org/abs/2011.13492
http://arxiv.org/abs/2011.13492