activity
20192026
most citedParallel Explicit Model Predictive Control

10 citations · 12 across the 10 of their papers we have counts for

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8 papers · 1 filter

eess.SY2026

On Piecewise Quadratic Terminal Costs for MPC

Sampath Kumar Mulagaleti, Boris Houska, Mario Zanon +1

This paper presents a novel approach to synthesize stabilizing termi- nal ingredients for linear model predictive control (MPC) schemes, with the aim of increasing the region of at…

eess.SY2025

Configuration-Constrained Tube MPC for Periodic Operation

Filippo Badalamenti, Jose A. Borja-Conde, Sampath Kumar Mulagaleti +3

Periodic operation often emerges as the economically optimal mode in industrial processes, particularly under varying economic or environmental conditions. This paper proposes a ro…

eess.SY20251 cited

Efficient Configuration-Constrained Tube MPC via Variables Restriction and Template Selection

Filippo Badalamenti, Sampath Kumar Mulagaleti, Mario Eduardo Villanueva +2

Configuration-Constrained Tube Model Predictive Control (CCTMPC) offers flexibility by using a polytopic parameterization of invariant sets and the optimization of an associated ve…

eess.SY20246 cited

Configuration-Constrained Tube MPC for Tracking

Filippo Badalamenti, Sampath Kumar Mulagaleti, Alberto Bemporad +2

This paper proposes a novel tube-based Model Predictive Control (MPC) framework for tracking varying setpoint references with linear systems subject to additive and multiplicative…

eess.SY2020

Online power system parameter estimation and optimal operation

Xu Du, Alexander Engelmann, Timm Faulwasser +1

The integration of renewables into electrical grids calls for optimization-based control schemes requiring reliable grid models. Classically, parameter estimation and optimization-…

eess.SY20202 cited

Distributed Optimization using ALADIN for MPC in Smart Grids

Yuning Jiang, Philipp Sauerteig, Boris Houska +1

This paper presents a distributed optimization algorithm tailored to solve optimization problems arising in smart grids. In detail, we propose a variant of the Augmented Lagrangian…