Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Fooladivanda, Dariush"'
Publikováno v:
IEEE Transactions on Automatic Control 2024
This paper proposes a novel approach to construct data-driven online solutions to optimization problems (P) subject to a class of distributionally uncertain dynamical systems. The introduced framework allows for the simultaneous learning of distribut
Externí odkaz:
http://arxiv.org/abs/2102.09111
We present a novel online learning algorithm for a class of unknown and uncertain dynamical environments that are fully observable. First, we obtain a novel probabilistic characterization of systems whose mean behavior is known but which are subject
Externí odkaz:
http://arxiv.org/abs/2009.02390
This paper studies a data-driven predictive control for a class of control-affine systems which is subject to uncertainty. With the accessibility to finite sample measurements of the uncertain variables, we aim to find controls which are feasible and
Externí odkaz:
http://arxiv.org/abs/1911.10184
Akademický článek
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A timely, accurate, and secure dynamic state estimation is needed for reliable monitoring and efficient control of microgrids. The synchrophasor technology enables us to obtain synchronized measurements in real-time and to develop dynamic state estim
Externí odkaz:
http://arxiv.org/abs/1908.05843
The performance of different combinations of user association (UA) and resource allocation (RA) in heterogeneous cellular networks has been extensively studied using a classic modeling approach based on system snapshots. There have been also many stu
Externí odkaz:
http://arxiv.org/abs/1903.08608
This paper introduces an optimization problem (P) and a solution strategy to design variable-speed-limit controls for a highway that is subject to traffic congestion and uncertain vehicle arrival and departure. By employing a finite data-set of sampl
Externí odkaz:
http://arxiv.org/abs/1810.11385
Renewable surplus power is increasing due to the increasing penetration of these intermittent resources. In practice, electric grid operators either curtail the surplus energy resulting from renewable-based generations or utilize energy storage resou
Externí odkaz:
http://arxiv.org/abs/1808.05046
This paper focuses on securely estimating the state of a nonlinear dynamical system from a set of corrupted measurements. In particular, we consider two broad classes of nonlinear systems, and propose a technique which enables us to perform secure st
Externí odkaz:
http://arxiv.org/abs/1603.06894
Publikováno v:
In Systems & Control Letters January 2019 123:47-54