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pro vyhledávání: '"Limon, Daniel"'
The main benefit of model predictive control (MPC) is its ability to steer the system to a given reference without violating the constraints while minimizing some objective. Furthermore, a suitably designed MPC controller guarantees asymptotic stabil
Externí odkaz:
http://arxiv.org/abs/2406.16496
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
A Model Predictive Controller for Tracking is introduced for rendezvous with non-cooperative tumbling targets in active debris removal applications. The target's three-dimensional non-periodic rotational dynamics as well as other state and control co
Externí odkaz:
http://arxiv.org/abs/2403.10986
Publikováno v:
in IEEE Control Systems Letters, vol. 8, pp. 1499-1504, 2024
Model Predictive Control (MPC) is a popular control approach due to its ability to consider constraints, including input and state restrictions, while minimizing a cost function. However, in practice, these constraints can result in feasibility issue
Externí odkaz:
http://arxiv.org/abs/2403.04601
The main objective of tracking control is to steer the tracking error, that is the difference between the reference and the output, to zero while the plant's operation limits are satisfied. This requires that some assumptions on the evolution of the
Externí odkaz:
http://arxiv.org/abs/2403.02973
Model Predictive Control (MPC) for tracking formulation presents numerous advantages compared to standard MPC, such as a larger domain of attraction and recursive feasibility even when abrupt changes in the reference are produced. As a drawback, it i
Externí odkaz:
http://arxiv.org/abs/2402.09912
Harmonic model predictive control (HMPC) is a recent model predictive control (MPC) formulation for tracking piece-wise constant references that includes a parameterized artificial harmonic reference as a decision variable, resulting in an increased
Externí odkaz:
http://arxiv.org/abs/2310.16723
Autor:
Nadales, Juan Moreno, Hakobyan, Astghik, de la Peña, David Muñoz, Limon, Daniel, Yang, Insoon
In the realm of maritime transportation, autonomous vessel navigation in natural inland waterways faces persistent challenges due to unpredictable natural factors. Existing scheduling algorithms fall short in handling these uncertainties, compromisin
Externí odkaz:
http://arxiv.org/abs/2310.14038
Autor:
Mirasierra, Victor, Limon, Daniel
In this paper, we present the periodic modifier-adaptation formulation of the dynamic real time optimization. The proposed formulation uses gradient information to update the problem with affine modifiers so that, upon convergence, its solution match
Externí odkaz:
http://arxiv.org/abs/2309.09680
Publikováno v:
IEEE Control Systems Letters, 2023
Model Predictive Control (MPC) is typically characterized for being computationally demanding, as it requires solving optimization problems online; a particularly relevant point when considering its implementation in embedded systems. To reduce the c
Externí odkaz:
http://arxiv.org/abs/2309.07996