Valentina Breschi

Autom., 2025

2024

Direct Data-Driven Design of LPV Controllers and Polytopic Invariant Sets With Cross-Covariance Noise Bounds.

[BibT_eX]

[DOI]

Manas Mejari

IEEE Control. Syst. Lett., 2024

On the Equivalence of Direct and Indirect Data-Driven Predictive Control Approaches.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2024

Exploiting structural observability and graph colorability for optimal sensor placement in water distribution networks.

[BibT_eX]

[DOI]

Jarne J. H. Van Gemert

CoRR, 2024

One controller to rule them all.

[BibT_eX]

[DOI]

CoRR, 2024

Bias correction and instrumental variables for direct data-driven model-reference control.

[BibT_eX]

[DOI]

CoRR, 2024

Optimal policy design for decision problems under social influence.

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

Aurelio Raffa Ugolini

Andrea Manzoni

Mara Tanelli

CoRR, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

Koopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees.

[BibT_eX]

[DOI]

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

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

[BibT_eX]

[DOI]

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

Hierarchical Model Predictive Control for Waste Heat Recovery in Steel Mills.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Control Technology and Applications, 2024

2023

Auto-tuning of reference models in direct data-driven control.

[BibT_eX]

[DOI]

Autom., September, 2023

On the Design of Regularized Explicit Predictive Controllers From Input-Output Data.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., August, 2023

Data-driven predictive control in a stochastic setting: a unified framework.

[BibT_eX]

[DOI]

Alessandro Chiuso

Autom., June, 2023

Handbook of linear data-driven predictive control: Theory, implementation and design.

[BibT_eX]

[DOI]

P. C. N. Verheijen

Mircea Lazar

Annu. Rev. Control., January, 2023

Data-Driven Model-Reference Control With Closed-Loop Stability: The Output-Feedback Case.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2023

Data-Driven Stabilization of Input-Saturated Systems.

[BibT_eX]

[DOI]

Luca Zaccarian

IEEE Control. Syst. Lett., 2023

Data-Driven Design of Explicit Predictive Controllers With Structural Priors.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

In-context learning of state estimators.

[BibT_eX]

[DOI]

CoRR, 2023

Model predictive control with dynamic move blocking.

[BibT_eX]

[DOI]

Alberto Leva

CoRR, 2023

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

[BibT_eX]

[DOI]

Riccardo Busetto

CoRR, 2023

Qualification and Quantification of Fairness for Sustainable Mobility Policies.

[BibT_eX]

[DOI]

Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

META-SMGO-$\Delta$: Similarity as a Prior in Black-Box Optimization.

[BibT_eX]

[DOI]

Riccardo Busetto

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

On the Impact of Regularization in Data-Driven Predictive Control.

[BibT_eX]

[DOI]

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Fostering the Mass Adoption of Electric Vehicles: A Network-Based Approach.

[BibT_eX]

[DOI]

IEEE Trans. Control. Netw. Syst., 2022

Direct data-driven design of LPV controllers with soft performance specifications.

[BibT_eX]

[DOI]

J. Frankl. Inst., 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

The role of regularization in data-driven predictive control.

[BibT_eX]

[DOI]

Alessandro Chiuso

CoRR, 2022

Noise Handling in Data-driven Predictive Control: A Strategy Based on Dynamic Mode Decomposition.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Smart Cities Conference, 2022

Data-driven design of explicit predictive controllers.

[BibT_eX]

[DOI]

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Learning explicit predictive controllers: theory and applications.

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

Autom., 2021

Designing Effective Policies to Drive the Adoption of Electric Vehicles: a Data-informed Approach.

[BibT_eX]

[DOI]

Proceedings of the 29th Mediterranean Conference on Control and Automation, 2021

Data-driven design of switching reference governors for brake-by-wire applications.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Laura Ferrarotti

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Direct data-driven model-reference control with Lyapunov stability guarantees.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

An ADMM-based approach for multi-class recursive parameter estimation.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Direct data-driven design of switching controllers for constrained systems.

[BibT_eX]

[DOI]

Proceedings of the 2021 American Control Conference, 2021

2020

Recursive Bias-Correction Method for Identification of Piecewise Affine Output-Error Models.

[BibT_eX]

[DOI]

Manas Mejari

IEEE Control. Syst. Lett., 2020

Estimation of jump Box-Jenkins models.

[BibT_eX]

[DOI]

Autom., 2020

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

[BibT_eX]

[DOI]

Autom., 2020

Cooperative constrained parameter estimation by ADMM-RLS.

[BibT_eX]

[DOI]

Autom., 2020

Direct Data-Driven Control with Embedded Anti-Windup Compensation.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Virtual Reference Feedback Tuning with data-driven reference model selection.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Social network analysis of electric vehicles adoption: a data-based approach.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Human-Machine Systems, 2020

Direct data-driven design of neural reference governors.

[BibT_eX]

[DOI]

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

NAW-NET: neural anti-windup control for saturated nonlinear systems.

[BibT_eX]

[DOI]

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Shrinkage Strategies for Structure Selection and Identification of Piecewise Affine Models.

[BibT_eX]

[DOI]

Manas Mejari

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019

Simulation-driven fixed-order controller tuning via moment matching.

[BibT_eX]

[DOI]

Proceedings of the 17th European Control Conference, 2019

Maximum-a-posteriori estimation of jump Box-Jenkins models.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018

Fitting jump models.

[BibT_eX]

[DOI]

Autom., 2018

Prediction error methods in learning jump ARMAX models.

[BibT_eX]

[DOI]

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Cloud-aided collaborative estimation by ADMM-RLS algorithms for connected diagnostics and prognostics.

[BibT_eX]

[DOI]

Proceedings of the 2018 Annual American Control Conference, 2018

2017

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

[BibT_eX]

[DOI]

CoRR, 2017

2016

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

[BibT_eX]

[DOI]

Autom., 2016

Identification of hybrid and linear parameter varying models via recursive piecewise affine regression and discrimination.

[BibT_eX]

[DOI]

Proceedings of the 15th European Control Conference, 2016

Learning hybrid models with logical and continuous dynamics via multiclass linear separation.

[BibT_eX]

[DOI]