Marco Forgione

发表

Run-to-Run Tuning of Model Predictive Control for Type 1 Diabetes Subjects: In Silico Trial

Marco Forgione, Claudio Cobelli, Lalo Magni, 2009, Journal of diabetes science and technology.

Experiment design for parameter estimation of a dynamical system in a nonlinear model structure based on multilevel excitation

H. Hjalmarsson, P. V. D. Hof, X. Bombois, 2013 .

NARX Identification using Derivative-Based Regularized Neural Networks

M. Schoukens, Marco Forgione, L. H. Peeters, 2022, ArXiv.

Roles of v-erbA homodimers and heterodimers in mediating dominant negative activity by v-erbA.

A. Sugawara, P. Yen, W. Chin, 1994, The Journal of biological chemistry.

Learning neural state-space models: do we need a state estimator?

D. Piga, Manas Mejari, Marco Forgione, 2022, ArXiv.

Data-drivenmodelimprovementformodel-basedcontrol

P. V. D. Hof, X. Bombois, Marco Forgione, 2013 .

NARX Identification using Derivative-Based Regularized Neural Networks

M. Schoukens, Marco Forgione, L. H. Peeters, 2022, 2022 IEEE 61st Conference on Decision and Control (CDC).

Triiodothyronine (T3) decreases binding to DNA by T3-receptor homodimers but not receptor-auxiliary protein heterodimers.

D. Darling, P. Yen, W. Chin, 1992, The Journal of biological chemistry.

Model Structures and Fitting Criteria for System Identification with Neural Networks

D. Piga, Marco Forgione, 2019, 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT).

Rapid Crystallization Process Development Strategy from Lab to Industrial Scale with PAT Tools in Skid Configuration

Marco Forgione, Herman J. M. Kramer, Peter J. Daudey, 2012 .

Efficient Calibration of Embedded MPC

A. Bemporad, D. Piga, Marco Forgione, 2019, ArXiv.

Performance-Oriented Model Learning for Data-Driven MPC Design

Alberto Bemporad, Marco Forgione, Simone Formentin, 2019, IEEE Control Systems Letters.

Batch-to-batch learning for model-based control of process systems with application to cooling crystallization

Marco Forgione, Marco Forgione, 2014 .

Continuous-time system identification with neural networks: model structures and fitting criteria

D. Piga, Marco Forgione, 2020, Eur. J. Control.

Integrated Neural Networks for Nonlinear Continuous-Time System Identification

Marco Forgione, Dario Piga, Bojan Mavkov, 2020, IEEE Control Systems Letters.

Neural State-Space Models: Empirical Evaluation of Uncertainty Quantification

D. Piga, Marco Forgione, 2023, IFAC-PapersOnLine.

Experiment design for parameter estimation in nonlinear systems based on multilevel excitation

Marco Forgione, Håkan Hjalmarsson, Xavier Bombois, 2014, 2014 European Control Conference (ECC).

Two-Stage Robot Controller Auto-Tuning Methodology for Trajectory Tracking Applications

D. Piga, L. Roveda, Marco Forgione, 2020 .

Batch-to-batch model improvement for cooling crystallization

P. V. D. Hof, X. Bombois, A. Mesbah, 2015 .

Data-driven model improvement for model-based control

Marco Forgione, Xavier Bombois, Paul M. J. Van den Hof, 2015, Autom..

Experiment design for batch-to-batch model-based learning control

Marco Forgione, Xavier Bombois, Paul M. J. Van den Hof, 2013, 2013 American Control Conference.

Propagation patterns of temporal spikes.

T A Pedley, R G Emerson, C A Turner, 1995, Electroencephalography and clinical neurophysiology.

Fast predictive visual servoing: A reference governor-based approach

E. Hoffman, D. Piga, Antonio Paolillo, 2023, Control Engineering Practice.

Learning Dynamical Systems From Quantized Observations: A Bayesian Perspective

D. Piga, Manas Mejari, Marco Forgione, 2022, IEEE Transactions on Automatic Control.

Robot control parameters auto-tuning in trajectory tracking applications

Marco Forgione, Dario Piga, Loris Roveda, 2020 .

dynoNet: A neural network architecture for learning dynamical systems pdf

Marco Forgione, Dario Piga, D. Piga, 2020, International Journal of Adaptive Control and Signal Processing.

Control Parameters Tuning Based on Bayesian Optimization for Robot Trajectory Tracking

Marco Forgione, Dario Piga, Loris Roveda, 2019 .

Do Reactive Post‐Resection “Injury” Spikes Exist?

R. Goodman, T. Schwartz, J. Bruce, 2000, Epilepsia.

In-context learning for model-free system identification

D. Piga, Marco Forgione, F. Pura, 2023, ArXiv.

On the adaptation of recurrent neural networks for system identification

Marco Forgione, Dario Piga, Marco Gallieri, 2022, Autom..

Deep learning with transfer functions: new applications in system identification pdf

Marco Forgione, Dario Piga, Manas Mejari, 2021, IFAC-PapersOnLine.

Least-costly experiment design for uni-parametric linear models: An analytical approach

Marco Forgione, P.M.J. Van den Hof, Xavier Bombois, 2015, 2015 European Control Conference (ECC).

A unified experiment design framework for detection and identification in closed-loop performance diagnosis

Marco Forgione, Håkan Hjalmarsson, Xavier Bombois, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).