Zobrazeno 1 - 10
of 1 725
pro vyhledávání: '"P. Zeilinger"'
Rank collapse, a phenomenon where embedding vectors in sequence models rapidly converge to a uniform token or equilibrium state, has recently gained attention in the deep learning literature. This phenomenon leads to reduced expressivity and potentia
Externí odkaz:
http://arxiv.org/abs/2410.10609
We propose a novel data-driven stochastic model predictive control framework for uncertain linear systems with noisy output measurements. Our approach leverages multi-step predictors to efficiently propagate uncertainty, ensuring chance constraint sa
Externí odkaz:
http://arxiv.org/abs/2409.10405
Learning uncertain dynamics models using Gaussian process~(GP) regression has been demonstrated to enable high-performance and safety-aware control strategies for challenging real-world applications. Yet, for computational tractability, most approach
Externí odkaz:
http://arxiv.org/abs/2409.08616
One of the most challenging tasks in control theory is arguably the design of a regulator for nonlinear systems when the dynamics are unknown. To tackle it, a popular strategy relies on finding a direct map between system responses and the controller
Externí odkaz:
http://arxiv.org/abs/2409.05685
Autor:
Sturm, E., Davies, R., Alves, J., Clénet, Y., Kotilainen, J., Monna, A., Nicklas, H., Pott, J. -U., Tolstoy, E., Vulcani, B., Achren, J., Annadevara, S., Anwand-Heerwart, H., Arcidiacono, C., Barboza, S., Barl, L., Baudoz, P., Bender, R., Bezawada, N., Biondi, F., Bizenberger, P., Blin, A., Boné, A., Bonifacio, P., Borgo, B., Born, J. van den, Buey, T., Cao, Y., Chapron, F., Chauvin, G., Chemla, F., Cloiseau, K., Cohen, M., Collin, C., Czoske, O., Dette, J. -O., Deysenroth, M., Dijkstra, E., Dreizler, S., Dupuis, O., van Egmond, G., Eisenhauer, F., Elswijk, E., Emslander, A., Fabricius, M., Fasola, G., Ferreira, F., Schreiber, N. M. Förster, Fontana, A., Gaudemard, J., Gautherot, N., Gendron, E., Gennet, C., Genzel, R., Ghouchou, L., Gillessen, S., Gratadour, D., Grazian, A., Grupp, F., Guieu, S., Gullieuszik, M., de Haan, M., Hartke, J., Hartl, M., Haussmann, F., Helin, T., Hess, H. -J., Hofferbert, R., Huber, H., Huby, E., Huet, J. -M., Ives, D., Janssen, A., Jaufmann, P., Jilg, T., Jodlbauer, D., Jost, J., Kausch, W., Kellermann, H., Kerber, F., Kravcar, H., Kravchenko, K., Kulcsár, C., Kunkarayakti, H., Kunst, P., Kwast, S., Lang, F., Lange, J., Lapeyrere, V., Ruyet, B. Le, Leschinski, K., Locatelli, H., Massari, D., Mattila, S., Mei, S., Merlin, F., Meyer, E., Michel, C., Mohr, L., Montargès, M., Müller, F., Münch, N., Navarro, R., Neumann, U., Neumayer, N., Neumeier, L., Pedichini, F., Pflüger, A., Piazzesi, R., Pinard, L., Porras, J., Portaluri, E., Przybilla, N., Rabien, S., Raffard, J., Raggazoni, R., Ramlau, R., Ramos, J., Ramsay, S., Raynaud, H. -F., Rhode, P., Richter, A., Rix, H. -W., Rodenhuis, M., Rohloff, R. -R., Romp, R., Rousselot, P., Sabha, N., Sassolas, B., Schlichter, J., Schuil, M., Schweitzer, M., Seemann, U., Sevin, A., Simioni, M., Spallek, L., Sönmez, A., Suuronen, J., Taburet, S., Thomas, J., Tisserand, E., Vaccari, P., Valenti, E., Kleijn, G. Verdoes, Verdugo, M., Vidal, F., Wagner, R., Wegner, M., van Winden, D., Witschel, J., Zanella, A., Zeilinger, W., Ziegleder, J., Ziegler, B.
MICADO is a first light instrument for the Extremely Large Telescope (ELT), set to start operating later this decade. It will provide diffraction limited imaging, astrometry, high contrast imaging, and long slit spectroscopy at near-infrared waveleng
Externí odkaz:
http://arxiv.org/abs/2408.16396
Direct volume rendering using ray-casting is widely used in practice. By using GPUs and applying acceleration techniques as empty space skipping, high frame rates are possible on modern hardware. This enables performance-critical use-cases such as vi
Externí odkaz:
http://arxiv.org/abs/2407.21552
We introduce data to predictive control, D2PC, a framework to facilitate the design of robust and predictive controllers from data. The proposed framework is designed for discrete-time stochastic linear systems with output measurements and provides a
Externí odkaz:
http://arxiv.org/abs/2407.17277
We present a stochastic predictive control framework for nonlinear systems subject to unbounded process noise with closed-loop guarantees. First, we first provide a conceptual shrinking-horizon framework that utilizes general probabilistic reachable
Externí odkaz:
http://arxiv.org/abs/2407.13257
Tube-based model predictive control (MPC) is the principal robust control technique for constrained linear systems affected by additive disturbances. While tube-based methods that compute the tubes online have been successfully applied to systems wit
Externí odkaz:
http://arxiv.org/abs/2406.12573
Autor:
Krupa, Pablo, Köhler, Johannes, Ferramosca, Antonio, Alvarado, Ignacio, Zeilinger, Melanie N., Alamo, Teodoro, Limon, Daniel
This paper provides a comprehensive tutorial on a family of Model Predictive Control (MPC) formulations, known as MPC for tracking, which are characterized by including an artificial reference as part of the decision variables in the optimization pro
Externí odkaz:
http://arxiv.org/abs/2406.06157