Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Agustina D'Jorge"'
Autor:
Ignacio J. Sánchez, Agustina D'Jorge, Alejandro C. Limache, Alejandro H. González, Antonio Ferramosca
Publikováno v:
International Journal of Robust and Nonlinear Control.
Publikováno v:
Mathematical Modelling, Simulations, and AI for Emergent Pandemic Diseases ISBN: 9780323950640
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::580d2905f2268af9334d738d2b1c2bed
https://doi.org/10.1016/b978-0-323-95064-0.00024-5
https://doi.org/10.1016/b978-0-323-95064-0.00024-5
Autor:
Manuel A. Acuña-Zegarra, Alma Y. Alanis, Francisco Aleman, Guillermo de Anda-Jáuregui, Sofia Bernal-Silva, Pablo Castañeda, Gerardo Chowell, Alexandre Colato, Andreu Comas-García, Ruth Corona-Moreno, Agustina D’Jorge, Liliana Durán-Polanco, Philip J. Gerrish, Alejandro H. González, Abba B. Gumel, Shuai Han, Mauricio Hernández-Ávila, Enrique Hernández-Lemus, Esteban A. Hernandez-Vargas, Yin Jiang, Gabriel Martinez-Soltero, Ramsés H. Mena, Rafael Meza, Calistus N. Ngonghala, Mayra Núñez-López, T.Y. Okosun, Ryosuke Omori, Gamaliel A. Palomo-Briones, Nancy F. Ramirez, Daniel Ríos-Rivera, Carlos E. Rodríguez, Erika E. Rodriguez Torres, Fernando Saldaña, Ignacio J. Sánchez, Mario Santana-Cibrian, Mario Siller, Sarah Skolnick, Anuj Srivastava, Horst Stoecker, Mayra R. Tocto-Erazo, Angélica Torres-Díaz, Jorge X. Velasco-Hernández, Lingxiao Wang, Rodrigo Zepeda-Tello, Kai Zhou
Publikováno v:
Mathematical Modelling, Simulations, and AI for Emergent Pandemic Diseases ISBN: 9780323950640
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c24c53002a05bf0f2852a1883c15f76
https://doi.org/10.1016/b978-0-323-95064-0.09993-0
https://doi.org/10.1016/b978-0-323-95064-0.09993-0
Autor:
Agustina D’Jorge, Alejandro Anderson, Antonio Ferramosca, Alejandro H. González, Marcelo Actis
Publikováno v:
Systems & Control Letters. 165:105244
Autor:
Ignacio E. Sánchez, Alejandro H. González, Guilherme V. Raffo, Antonio Ferramosca, Agustina D'Jorge
Publikováno v:
Journal of Intelligent & Robotic Systems. 102
In the control systems community, path-following refers to the problem of tracking an output reference curve. This work presents a novel model predictive path-following control formulation for nonlinear systems with constraints, extended with an obst
Autor:
Juan E. Sereno, Esteban A. Hernandez-Vargas, Agustina D'Jorge, Antonio Ferramosca, Alejandro H. González
Publikováno v:
IFAC-Papers
Social distancing strategies have been adopted by governments to manage the COVID-19 pandemic, since the first outbreak began. However, further epidemic waves keep out the return of economic and social activities to their standard levels of intensity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36a9385ac0f5bedb8a52c3b7dad70c22
http://hdl.handle.net/10446/199442
http://hdl.handle.net/10446/199442
Autor:
Ignacio J. R. Sánchez, Antonio Ferramosca, Agustina D'Jorge, Alejandro Cesar Limache, Alejandro H. González
Publikováno v:
2020 Argentine Conference on Automatic Control (AADECA).
In this paper, a new model predictive controller for path following of periodic references is proposed. This controller combines trajectory planning and tracking stages in a single optimization problem for a given periodic parametric path. In additio
Autor:
Alejandro H. Gonzlez, Agustina D'Jorge, Antonio Ferramosca, Ignacio E. Sánchez, Guilherme V. Raffo
Publikováno v:
2019 XVIII Workshop on Information Processing and Control (RPIC).
In this article, the path following and trajectory tracking problems for constrained vehicles are tackled by means of a unified Model Predictive Control strategy. State and input constraints are taken into account, and additional artificial variables
Autor:
Guilherme V. Raffo, Antonio Ferramosca, Agustina D'Jorge, Ignacio E. Sánchez, Alejandro H. González
Publikováno v:
ICAR
This work presents a model predictive formulation for obstacle avoiding path following control for constrained vehicles. The obstacles are introduced as soft constraints in the value function, in order to maintain the convexity of state and output sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::accbe4714e3764d7332fd2e06bb52b45
http://hdl.handle.net/10446/169402
http://hdl.handle.net/10446/169402
Autor:
Antonio Ferramosca, Agustina D'Jorge, Alejandro H. González, Alejandro Anderson, Ernesto Kofman
Publikováno v:
2018 Argentine Conference on Automatic Control (AADECA).
The understanding of invariant set theory is essential in the design of controllers for constrained systems. This paper presents some concepts related with the invariant set theory and Set-Based Model Predictive Control (set-based MPC). Precisely, in