6 citations · 13 across the 13 of their papers we have counts for
8 papers · 1 filter
Identification of contractive Lur'e-type systems via kernel-based Lipschitz design
Cesare Donati, Fabrizio Dabbene, Constantino Lagoa +2
This paper addresses the problem of identifying contractive Lur'e-type systems. Specifically, it proposes an identification framework that integrates linear prior knowledge with a…
MPC-based motion planning for non-holonomic systems in non-convex domains
Matthias Lorenzen, Teodoro Alamo, Martina Mammarella +1
Motivated by the application of using model predictive control (MPC) for motion planning of autonomous mobile robots, a form of output tracking MPC for non-holonomic systems and wi…
A kernel-based approach to physics-informed nonlinear system identification
Cesare Donati, Martina Mammarella, Giuseppe C. Calafiore +3
This paper presents a kernel-based framework for physics-informed nonlinear system identification. The key contribution is a structured methodology that extends kernel-based techni…
Recursive feasibility for stochastic MPC and the rationale behind fixing flat tires
Mirko Fiacchini, Martina Mammarella, Fabrizio Dabbene
In this paper, we address the problem of designing stochastic model predictive control (SMPC) schemes for linear systems affected by unbounded disturbances. The contribution of the…
A Model-based Approach for Glucose Control via Physical Activity
Pierluigi Francesco De Paola, Alessandro Borri, Alessia Paglialonga +2
The role played by physical activity in slowing down the progression of type-2 diabetes is well recognized. However, except for general clinical guidelines, quantitative real-time…
Recovering nonlinear dynamics from non-uniform observations: A physics-based identification approach with practical case studies
Cesare Donati, Martina Mammarella, Fabrizio Dabbene +2
Uniform and smooth data collection is often infeasible in real-world scenarios. In this paper, we propose an identification framework to effectively handle the so-called non-unifor…
A control system framework for counterfactuals: an optimization based approach
Pierluigi Francesco De Paola, Jared Miller, Alessandro Borri +2
Counterfactuals are a concept inherited from the field of logic and in general attain to the existence of causal relations between sentences or events. In particular, this concept…
Closed-loop robust control of long-term diabetes progression via physical activity management
Pierluigi Francesco De Paola, Alessandro Borri, Fabrizio Dabbene +2
Large clinical evidence acknowledges the crucial role played by physical activity in delaying the progression of type-2 diabetes. However, the literature lacks control approaches t…