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of 2 792
pro vyhledávání: '"Wouw, A"'
This work proposes a hybrid model- and data-based scheme for fault detection, isolation, and estimation (FDIE) for a class of wafer handler (WH) robots. The proposed hybrid scheme consists of: 1) a linear filter that simultaneously estimates system s
Externí odkaz:
http://arxiv.org/abs/2412.09114
Autor:
van Peijpe, Casper, Ghanipoor, Farhad, de Loore, Youri, Hacking, Pim, van de Wouw, Nathan, Esfahani, Peyman Mohajerin
This paper presents a mathematical framework for modeling the dynamic effects of three fault categories and six fault variants in the ink channels of high-end industrial printers. It also introduces a hybrid approach that combines model-based and dat
Externí odkaz:
http://arxiv.org/abs/2412.07545
This paper introduces the concept of abstracted model reduction: a framework to improve the tractability of structure-preserving methods for the complexity reduction of interconnected system models. To effectively reduce high-order, interconnected mo
Externí odkaz:
http://arxiv.org/abs/2411.13344
With the goal of increasing the speed and efficiency in robotic manipulation, a control approach is presented that aims to utilize intentional simultaneous impacts to its advantage. This approach exploits the concept of the time-invariant reference s
Externí odkaz:
http://arxiv.org/abs/2411.09870
Impact-aware robotic manipulation benefits from an accurate map from ante-impact to post-impact velocity signals to support, e.g., motion planning and control. This work proposes an approach to generate and experimentally validate such impact maps fr
Externí odkaz:
http://arxiv.org/abs/2411.06319
Federated learning (FL) has emerged as a method to preserve privacy in collaborative distributed learning. In FL, clients train AI models directly on their devices rather than sharing data with a centralized server, which can pose privacy risks. Howe
Externí odkaz:
http://arxiv.org/abs/2409.17201
Structural dynamics models with nonlinear stiffness appear, for example, when analyzing systems with nonlinear material behavior or undergoing large deformations. For complex systems, these models become too large for real-time applications or multi-
Externí odkaz:
http://arxiv.org/abs/2407.21672
To improve the predictive capacity of system models in the input-output sense, this paper presents a framework for model updating via learning of modeling uncertainties in locally (and thus also in globally) Lipschitz nonlinear systems. First, we int
Externí odkaz:
http://arxiv.org/abs/2406.06116
Many state-of-the-art methods for safety assessment and motion planning for automated driving require estimation of the probability of collision (POC). To estimate the POC, a shape approximation of the colliding actors and probability density functio
Externí odkaz:
http://arxiv.org/abs/2405.10765
To enhance the robustness of cooperative driving to cyberattacks, we study a controller-oriented approach to mitigate the effect of a class of False-Data Injection (FDI) attacks. By reformulating a given dynamic Cooperative Adaptive Cruise Control sc
Externí odkaz:
http://arxiv.org/abs/2404.05361