Searched for: subject%3A%22dependence%255C+uncertainty%22
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Tao, T. (author)
This thesis deals with the adaptive control of interconnected systems and multi-agent systems, where adaptive control is used to deal with the presence of uncertainties. Generally, two types of uncertainties can occur. The first one is parametric uncertainty, which is most commonly addressed in the literature, and for which several design...
doctoral thesis 2022
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Li, Peng (author), Liu, Di (author), Baldi, S. (author)
Adaptive integral sliding mode control (AISMC) is an extension of adaptive sliding mode control which is a way to ensure sliding motion while handling system uncertainties. However, conventional AISMC formulations require to different extent a priori knowledge of the system uncertainty: either the upper bound of the uncertainty or of its time...
journal article 2022
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Bartl, Daniel (author), Kupper, Michael (author), Lux, Thibaut (author), Papapantoleon, A. (author)
Motivated by applications in model-free finance and quantitative risk management, we consider Frechet classes of multivariate distribution functions where additional information on the joint distribution is assumed, while uncertainty in the marginals is also possible. We derive optimal transport duality results for these Frechet classes that...
journal article 2022
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Roy, S. (author), Lee, Jinoh (author), Baldi, S. (author)
This brief proposes a new adaptive-robust formulation for time-delay control (TDC) under a less-restrictive stability condition. TDC relies on estimating the unknown system dynamics via the artificial introduction of a time delay, often referred to as time-delay estimation (TDE). In conventional TDC, the estimation error, called TDE error, is...
journal article 2021
Searched for: subject%3A%22dependence%255C+uncertainty%22
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