12 citations · 25 across the 8 of their papers we have counts for
8 papers
Regularized Gauss-Newton for Optimizing Overparameterized Neural Networks
Adeyemi D. Adeoye, Philipp Christian Petersen, Alberto Bemporad
The generalized Gauss-Newton (GGN) optimization method incorporates curvature estimates into its solution steps, and provides a good approximation to the Newton method for large-sc…
Data-Driven Synthesis of Configuration-Constrained Robust Invariant Sets for Linear Parameter-Varying Systems
Manas Mejari, Sampath Kumar Mulagaleti, Alberto Bemporad
We present a data-driven method to synthesize robust control invariant (RCI) sets for linear parameter-varying (LPV) systems subject to unknown but bounded disturbances. A finite-l…
Computation of safe disturbance sets using implicit RPI sets
Sampath Kumar Mulagaleti, Alberto Bemporad, Mario Zanon
Given a stable linear time-invariant (LTI) system subject to output constraints, we present a method to compute a set of disturbances such that the reachable set of outputs matches…
Specification-Guided Critical Scenario Identification for Automated Driving
Adam Molin, Edgar A. Aguilar, Dejan Ničković +3
To test automated driving systems, we present a case study for finding critical scenarios in driving environments guided by formal specifications. To that aim, we devise a framewor…
A construction-free coordinate-descent augmented-Lagrangian method for embedded linear MPC based on ARX models
Liang Wu, Alberto Bemporad
This paper proposes a construction-free algorithm for solving linear MPC problems based on autoregressive with exogenous terms (ARX) input-output models. The solution algorithm rel…
Stochastic economic model predictive control for Markovian switching systems
Pantelis Sopasakis, Domagoj Herceg, Panagiotis Patrinos +1
The optimization of process economics within the model predictive control (MPC) formulation has given rise to a new control paradigm known as economic MPC (EMPC). Several authors h…