1 code implementation • 21 Mar 2024 • Marco Forgione, Manas Mejari, Dario Piga
With a specific emphasis on control design objectives, achieving accurate system modeling with limited complexity is crucial in parametric system identification.
1 code implementation • 8 Mar 2024 • Dario Piga, Matteo Rufolo, Gabriele Maroni, Manas Mejari, Marco Forgione
This paper addresses the challenge of overfitting in the learning of dynamical systems by introducing a novel approach for the generation of synthetic data, aimed at enhancing model generalization and robustness in scenarios characterized by data scarcity.
no code implementations • 21 Sep 2023 • Francesca Venturini, Silvan Fluri, Manas Mejari, Michael Baumgartner, Dario Piga, Umberto Michelucci
This work systematically investigates the oxidation of extra virgin olive oil (EVOO) under accelerated storage conditions with UV absorption and total fluorescence spectroscopy.
no code implementations • 13 Sep 2023 • 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.
no code implementations • 5 Sep 2023 • Sampath Kumar Mulagaleti, Manas Mejari, Alberto Bemporad
We present a method to synthesize parameter-dependent robust control invariant (PD-RCI) sets for LPV systems with bounded parameter variation, in which invariance is induced using PD-vertex control laws.
no code implementations • 4 Sep 2023 • Manas Mejari, Ankit Gupta, Dario Piga
We present a direct data-driven approach to synthesize robust control invariant (RCI) sets and their associated gain-scheduled feedback control laws for linear parameter-varying (LPV) systems subjected to bounded disturbances.
no code implementations • 31 Mar 2023 • Manas Mejari, Ankit Gupta
This paper presents a direct data-driven approach for computing robust control invariant (RCI) sets and their associated state-feedback control laws for linear time-invariant systems affected by bounded disturbances.
no code implementations • 4 Oct 2022 • Manas Mejari, Dario Piga
The key idea for direct CT identification is based on an integral architecture consisting of an LSS model followed by an integral block.
5 code implementations • 26 Jun 2022 • Marco Forgione, Manas Mejari, Dario Piga
In recent years, several algorithms for system identification with neural state-space models have been introduced.
1 code implementation • 20 Apr 2021 • Dario Piga, Marco Forgione, Manas Mejari
The dynamical operator is included as {the} last layer of a neural network in order to obtain the optimal one-step-ahead prediction error.
no code implementations • 21 Sep 2020 • Ankit Gupta, Manas Mejari, Paolo Falcone, Dario Piga
This paper presents an iterative algorithm to compute a Robust Control Invariant (RCI) set, along with an invariance-inducing control law, for Linear Parameter-Varying (LPV) systems.