25 citations · 44 across the 12 of their papers we have counts for
14 papers
Model predictive control for tracking using artificial references: Fundamentals, recent results and practical implementation
Pablo Krupa, Johannes Köhler, Antonio Ferramosca +4
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 artifici…
Model Predictive Control for setpoint tracking
Daniel Limon, Antonio Ferramosca, Ignacio Alvarado +1
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 s…
Set-Point Tracking MPC with Avoidance Features
Marcelo A. Santos, Antonio Ferramosca, Guilherme V. Raffo
This work proposes a finite-horizon optimal control strategy to solve the tracking problem while providing avoidance features to the closed-loop system. Inspired by the set-point t…
A unified surrogate-based scheme for black-box and preference-based optimization
Davide Previtali, Mirko Mazzoleni, Antonio Ferramosca +1
Black-box and preference-based optimization algorithms are global optimization procedures that aim to find the global solutions of an optimization problem using, respectively, the…
GLISp-r: A preference-based optimization algorithm with convergence guarantees
Davide Previtali, Mirko Mazzoleni, Antonio Ferramosca +1
Preference-based optimization algorithms are iterative procedures that seek the optimal calibration of a decision vector based only on comparisons between couples of different tuni…
Minimizing the Epidemic Final Size while Containing the Infected Peak Prevalence in SIR Systems
J. Sereno, A. L. Anderson, A. Ferramosca +2
Mathematical models are instrumental to forecast the spread of pathogens and to evaluate the effectiveness of non-pharmaceutical measures. A plethora of optimal strategies has been…
Optimal control strategies to tailor antivirals for acute infectious diseases in the host
Mara Perez, Pablo Abuin, Marcelo Actis +3
Several mathematical models in SARS-CoV-2 have shown how target-cell model can help to understand the spread of the virus in the host and how potential candidates of antiviral trea…
Model predictive control for optimal social distancing in a type SIR-switched model
J. E. Sereno, A. D' Jorge, A. Ferramosca +2
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 o…
Dynamic characterization of control SIR-type systems and optimal single-interval control
A. H. González, A. L. Anderson, A. Ferramosca +1
Although modeling studies are focused on the control of SIR-based systems describing epidemic data sets (particularly the COVID-19), few of them present a formal dynamic characteri…
Dynamical Characterization of Antiviral Effects in COVID-19
Pablo Abuin, Alejandro Anderson, Antonio Ferramosca +2
Mathematical models describing SARS-CoV-2 dynamics and the corresponding immune responses in patients with COVID-19 can be critical to evaluate possible clinical outcomes of antivi…
On stability of nonzero set-point for non linear impulsive control systems
A. D'Jorge, A. L. Anderson, A. Ferramosca +2
The interest in non-linear impulsive systems (NIS) has been growing due to its impact in application problems such as disease treatments (diabetes, HIV, influenza, among many other…
Discrete-time MPC for switched systems with applications to biomedical problems
Alejandro Anderson, Alejandro Hernan Gonzalez, Antonio Ferramosca +1
Switched systems in which the manipulated control action is the time-depending switching signal describe many engineering problems, mainly related to biomedical applications. In su…
Characterization of SARS-CoV-2 Dynamics in the Host
Pablo Abuin, Alejandro Anderson, Antonio Ferramosca +2
While many epidemiological models have being proposed to understand and handle COVID-19, too little has been invested to understand how the virus replicates in the human body and p…
Set-based MPC for discrete-time LTI systems with maximal domain of attraction and minimal predictive control horizon
Alejandro Anderson, Agustina D'Jorge, Alejandro H. González +2
This paper presents a novel set-based model predictive control for tracking, which provides the largest domain of attraction, even with the minimal predictive/control horizon. The…