most citedLearning Quasi-LPV Models and Robust Control Invariant Sets with Reduced Conservativeness

1 citations · 1 across the 4 of their papers we have counts for

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6 papers

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.SY2025

A Regularization and Active Learning Method for Identification of Quasi Linear Parameter Varying Systems

Sampath Kumar Mulagaleti, Alberto Bemporad

This paper proposes an active learning method for designing experiments to identify quasi-Linear Parameter-Varying (qLPV) models. Since informative experiments are costly, input si…

eess.SY2025

Sample Efficient Certification of Discrete-Time Control Barrier Functions

Sampath Kumar Mulagaleti, Andrea Del Prete

Control Invariant (CI) sets are instrumental in certifying the safety of dynamical systems. Control Barrier Functions (CBFs) are effective tools to compute such sets, since the zer…

eess.SY2025

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…

math.OC20251 cited

Learning Quasi-LPV Models and Robust Control Invariant Sets with Reduced Conservativeness

Sampath Kumar Mulagaleti, Alberto Bemporad

We present an approach to identify a quasi Linear Parameter Varying (qLPV) model of a plant, with the qLPV model guaranteed to admit a robust control invariant (RCI) set. It builds…

eess.SY2024

Combined Learning of Linear Parameter-Varying Models and Robust Control Invariant Sets

Sampath Kumar Mulagaleti, Alberto Bemporad

Dynamical models identified from data are frequently employed in control system design. However, decoupling system identification from controller synthesis can result in situations…