4 papers
Self-concordant smoothing in proximal quasi-Newton algorithms for large-scale convex composite optimization
Adeyemi D. Adeoye, Alberto Bemporad
We introduce a notion of self-concordant smoothing for minimizing the sum of two convex functions, one of which is smooth and the other nonsmooth. The key highlight is a natural pr…
Harmonic model predictive control for tracking sinusoidal references and its application to trajectory tracking
Pablo Krupa, Daniel Limon, Alberto Bemporad +1
Harmonic model predictive control (HMPC) is a recent model predictive control (MPC) formulation for tracking piece-wise constant references that includes a parameterized artificial…
Global and Preference-based Optimization with Mixed Variables using Piecewise Affine Surrogates
Mengjia Zhu, Alberto Bemporad
Optimization problems involving mixed variables (i.e., variables of numerical and categorical nature) can be challenging to solve, especially in the presence of mixed-variable cons…
An active learning method for solving competitive multi-agent decision-making and control problems
Filippo Fabiani, Alberto Bemporad
To identify a stationary action profile for a population of competitive agents, each executing private strategies, we introduce a novel active-learning scheme where a centralized e…