Valentina Breschi

Orcid: 0000-0002-1533-7349

According to our database1, Valentina Breschi authored at least 54 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Meta-learning of data-driven controllers with automatic model reference tuning: theory and experimental case study.
CoRR, 2024

On the equivalence of direct and indirect data-driven predictive control approaches.
CoRR, 2024

SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study.
CoRR, 2024

Explainable data-driven modeling via mixture of experts: towards effective blending of grey and black-box models.
CoRR, 2024

2023
Auto-tuning of reference models in direct data-driven control.
Autom., September, 2023

On the Design of Regularized Explicit Predictive Controllers From Input-Output Data.
IEEE Trans. Autom. Control., August, 2023

Data-driven predictive control in a stochastic setting: a unified framework.
Autom., June, 2023

Handbook of linear data-driven predictive control: Theory, implementation and design.
Annu. Rev. Control., January, 2023

Data-Driven Model-Reference Control With Closed-Loop Stability: The Output-Feedback Case.
IEEE Control. Syst. Lett., 2023

Data-Driven Stabilization of Input-Saturated Systems.
IEEE Control. Syst. Lett., 2023

Data-Driven Design of Explicit Predictive Controllers With Structural Priors.
IEEE Control. Syst. Lett., 2023

Harnessing the Final Control Error for Optimal Data-Driven Predictive Control.
CoRR, 2023

In-context learning of state estimators.
CoRR, 2023

Meta-learning for model-reference data-driven control.
CoRR, 2023

Model predictive control with dynamic move blocking.
CoRR, 2023

META-SMGO-Δ: similarity as a prior in black-box optimization.
CoRR, 2023

Qualification and Quantification of Fairness for Sustainable Mobility Policies.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

META-SMGO-$\Delta$: Similarity as a Prior in Black-Box Optimization.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

On the Impact of Regularization in Data-Driven Predictive Control.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Fostering the Mass Adoption of Electric Vehicles: A Network-Based Approach.
IEEE Trans. Control. Netw. Syst., 2022

Direct data-driven design of LPV controllers with soft performance specifications.
J. Frankl. Inst., 2022

Uncertainty-aware data-driven predictive control in a stochastic setting.
CoRR, 2022

Data-driven design of explicit predictive controllers using model-based priors.
CoRR, 2022

The role of regularization in data-driven predictive control.
CoRR, 2022

Noise Handling in Data-driven Predictive Control: A Strategy Based on Dynamic Mode Decomposition.
Proceedings of the Learning for Dynamics and Control Conference, 2022

Sharing-DNA: a data-driven tool to map the attitude towards sharing services across Europe.
Proceedings of the IEEE International Smart Cities Conference, 2022

Data-driven design of explicit predictive controllers.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Learning explicit predictive controllers: theory and applications.
CoRR, 2021

Model structure selection for switched NARX system identification: A randomized approach.
Autom., 2021

Designing Effective Policies to Drive the Adoption of Electric Vehicles: a Data-informed Approach.
Proceedings of the 29th Mediterranean Conference on Control and Automation, 2021

Data-driven design of switching reference governors for brake-by-wire applications.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

The benefits of sharing: a cloud-aided performance-driven framework to learn optimal feedback policies.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Direct data-driven model-reference control with Lyapunov stability guarantees.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

An ADMM-based approach for multi-class recursive parameter estimation.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Direct data-driven design of switching controllers for constrained systems.
Proceedings of the 2021 American Control Conference, 2021

2020
Recursive Bias-Correction Method for Identification of Piecewise Affine Output-Error Models.
IEEE Control. Syst. Lett., 2020

Estimation of jump Box-Jenkins models.
Autom., 2020

Vehicle sideslip estimation via kernel-based LPV identification: Theory and experiments.
Autom., 2020

Cooperative constrained parameter estimation by ADMM-RLS.
Autom., 2020

Direct Data-Driven Control with Embedded Anti-Windup Compensation.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Virtual Reference Feedback Tuning with data-driven reference model selection.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Social network analysis of electric vehicles adoption: a data-based approach.
Proceedings of the IEEE International Conference on Human-Machine Systems, 2020

Direct data-driven design of neural reference governors.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

NAW-NET: neural anti-windup control for saturated nonlinear systems.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Shrinkage Strategies for Structure Selection and Identification of Piecewise Affine Models.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019
Simulation-driven fixed-order controller tuning via moment matching.
Proceedings of the 17th European Control Conference, 2019

Maximum-a-posteriori estimation of jump Box-Jenkins models.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
Fitting jump models.
Autom., 2018

Prediction error methods in learning jump ARMAX models.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Cloud-aided collaborative estimation by ADMM-RLS algorithms for connected diagnostics and prognostics.
Proceedings of the 2018 Annual American Control Conference, 2018

2017
Cloud-aided collaborative estimation by ADMM-RLS algorithms for connected vehicle prognostics.
CoRR, 2017

2016
Piecewise affine regression via recursive multiple least squares and multicategory discrimination.
Autom., 2016

Identification of hybrid and linear parameter varying models via recursive piecewise affine regression and discrimination.
Proceedings of the 15th European Control Conference, 2016

Learning hybrid models with logical and continuous dynamics via multiclass linear separation.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016


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