Publications
[1]
La Bella, M. Farina, W. D'Amico, L. Zaccarian. Regional stability conditions for recurrent
neural network-based control systems. Automatica. Volume 174, paper n. 112127, 2025.
[2]
La Bella, W. D'Amico, M. Farina.
Data-driven control of echo state-based recurrent neural networks with robust
stability guarantees. Systems &
Control Letters. Volume 195, paper n. 105974, 2025.
[3]
D. Ravasio,
M. Farina, A. Ballarino. LMI-Based Design of a Robust Model Predictive
Controller for a Class of Recurrent Neural Networks With
Guaranteed Properties. IEEE Control
Systems Letters, vol. 8, pp. 1126-1131, 2024.
[4]
Mark, D. Ravasio,
M. Farina, D. Görges. Stochastic MPC for Linear
Systems With Unbounded Multiplicative Noise
Guaranteeing Closed-Loop Chance Constraints Satisfaction. IEEE Control Systems Letters, vol. 8, pp. 2081-2086, 2024.
[5]
M. Farina, E. Lettieri,
T Filippi, F. Zoccarato, P.
Perego, A. Di Francesco and G. Toletti.
The freedom to run: developing an autonomous robot matching the needs of
visually impaired citizens to technology opportunities. Disability and Rehabilitation: Assistive Technology, 20(2), pp. 370–380,
2024.
[6]
W. D'Amico, A. La Bella, M. Farina.
An incremental input-to-state stability condition for a generic class of recurrent
neural networks. IEEE Transactions on
Automatic Control. vol. 69, no. 4, pp. 2221-2236, 2024.
[7]
F. Bonassi,
A. La Bella, M. Farina, R. Scattolini. Nonlinear MPC
design for incrementally ISS systems with application to GRU networks. Automatica.
Volume 159, n. 111381, 2024.
[8]
W. D'Amico, M. Farina. Virtual
Reference Feedback Tuning for linear discrete-time systems with robust
stability guarantees based on Set Membership. Automatica, Volume 157, n.
1112282023, 2023.
[9]
J. Xie, F. Bonassi, M. Farina, R. Scattolini.
Robust offset-free nonlinear model predictive control for systems learned by
neural nonlinear autoregressive exogenous models. International Journal of Robust and Nonlinear Control, 33(16), pp.
9992–10009, 2023.
[10] W. D'Amico, A. Bisoffi, M.
Farina. Data-based control design for output-error linear discrete-time systems
with probabilistic stability guarantees. Control
Systems Letters, Volume 7, pp. 2035 - 2040, 2023.
[11] M. Farina, M. Rocca. A novel distributed algorithm for
estimation and control of large-scale systems. European Journal of Control. Volume 72, paper n. 100820, 2023.
[12] Rebecchi, M. Farina, G. Andreoni, S.
Capolongo, M. Corno, P. Perego, E. Lettieri. Shaping
accessible public spaces for visually impaired people. The BUDD-e research
experience. Dar forma a spazi pubblici
accessibili per le persone
con limitazioni visive. L’esperienza
di ricerca BUDD-e. Journal of Technology for Architecture and Environment (TECHNE), n.
25, pp. 192-203, 2023.
[13] L. Bascetta,
M. Farina, A. Gabrielli, M. Matteucci. A feedback linearisation algorithm for
single-track models with structural stability properties. Control Engineering Practice, Volume 128, paper n. 105318, 2022.
[14] F. Bonassi, M.
Farina, J. Xie and R. Scattolini. On
Recurrent Neural Networks for learning-based control: recent results and ideas
for future developments. Journal of
Process Control, Volume 114, pp. 92-104, 2022.
[15] F. Bonassi, M.
Farina, R. Scattolini. On the stability properties of Gated
Recurrent Units neural networks. Systems
& Control Letters. Volume 157, 2021.
[16] M. Farina, A. Caspani.
Model-based fault isolability and isolation of
persistent faults: centralized and distributed implementations. System & control letters. Volume
156, 2021.
[17] S. Spinelli,
M. Farina, and A. Ballarino. A Hierarchical Architecture for
Optimal Unit Commitment and Control of an Ensemble of Steam Generators. IEEE Transactions on Control System
Technology. Volume 30 (3), pp. 1145-1158, 2021.
[18] E. Terzi, M.
Farina, L. Fagiano, R. Scattolini. Robust
multi-rate predictive control using multi-step prediction models learned from
data. Automatica.
Vol. 136, paper n. 109852, 2021.
[19] M. Pezzutto,
M. Farina, R. Carli and L. Schenato. Remote
MPC for Tracking Over Lossy Networks. IEEE
Control Systems Letters, vol. 6, pp. 1040-1045, 2021.
[20]
F. Bonassi, M. Farina, R. Scattolini. On the stability properties of Gated Recurrent Units
neural networks. Systems & Control
Letters, Volume 157, 2021.
[21] M. Farina, A. Caspani,
Model-based fault isolability and isolation of
persistent faults: Centralized and distributed implementations, Systems & Control Letters, Volume
156, 2021.
[22]
E. Terzi, F. Bonassi, M. Farina, R. Scattolini. Learning model predictive control with long short-term
memory networks. International Journal of
Robust and Nonlinear Control, Volume 31, pp 8877-8896, 2021.
[23]
S. Spinelli, M. Farina and A. Ballarino. An optimal hierarchical control scheme for smart
generation units: an application to combined steam and electricity generation. Journal of Process Control, 94, pp.
58-74, 2020.
[24]
D. Bicego, J. Mazzetto, M. Farina, R. Carli, A. Franchi. Nonlinear Model Predictive Control with Enhanced
Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs. Journal of Intelligent & Robotic Systems.
vol. 100, pp.1213-1247, 2020.
[25]
E. Terzi, T. Bonetti, D. Saccani, M. Farina, L. Fagiano, R.
Scattolini. Learning-based predictive control of
the cooling system of a large business centre. Control Engineering Practice. Volume 97,
2020.
[26]
E. Terzi, L. Fagiano, M. Farina, R. Scattolini. Structured modelling from data and optimal control of
the cooling system of a large business center. Journal of Building Engineering, Volume 28, 2020.
[27]
M. Lauricella, M. Farina, R. Schneider, R. Scattolini. Iterative distributed fault detection and isolation
for linear systems based on Moving Horizon Estimation. International Journal of Adaptive Control and Signal Processing,
2020, Volume 34, Issue 6, pp 743-756.
[28]
A. La Bella, M. Farina, C. Sandroni, R. Scattolini. Design of Aggregators for the Day-Ahead Management of
Microgrids Providing Active and Reactive Power Services. IEEE Transactions on Control Systems Technology, 2020, Volume 28
(6), pp. 2616-2624.
[29]
L. Bugliari Armenio, E. Terzi, M. Farina, R. Scattolini. Model Predictive Control Design for Dynamical Systems
Learned by Echo State Networks. IEEE
Control Systems Letters (L-CSS), Volume 3, Issue 4, 2019, pp. 1044-1049.
[30]
E. Terzi, L. Fagiano, M. Farina, R. Scattolini. Learning-based predictive control for linear systems:
a unitary approach. Automatica.
Volume 108, 2019, pp. 1-13.
[31] M. Farina, X.
Zhang, R. Scattolini. A hierarchical MPC scheme for
coordination of independent systems with shared resources and plug-and-play capabilities.
IEEE Transactions on Control System
Technology, 28(2), 2020.
[32]
F. Boem, R. Carli, M. Farina, G. Ferrari Trecate, T.
Parisini. Distributed Fault Detection for
Interconnected Large-Scale Systems: A Scalable Plug \& Play Approach. IEEE Transactions on Control of Network
Systems. Volume 6(12), 2019, pp. 800-811.
[33]
X. Zhang, M. Farina, S. Spinelli, R. Scattolini. A multi-rate Model Predictive Control algorithm for
systems with fast-slow dynamics. IET
Control Theory and applications. Volume 12(18), 2018, pp. 2468-2477.
[34]
G. Bardaro, L. Bascetta, E. Ceravolo, M. Farina, M.
Gabellone, M. Matteucci. MPC-based control architecture of an
autonomous wheelchair for indoor environments. Control Engineering Practice. Volume 78, 2018, pp. 160-174.
[35]
M. Farina, X. Zhang, R. Scattolini. A hierarchical multi-rate MPC scheme for interconnected systems. Automatica.
Volume 90, 2018, pp. 38-46.
[36]
M. Farina, S. Misiano.
Stochastic Distributed Predictive Tracking Control for Networks of Autonomous
Systems With Coupling Constraints. IEEE Transactions on Control of Network
Systems. Volume 5(3), 2018, pp. 1412-1423.
[37]
M. Farina, R. Carli. Partition-based
Distributed Kalman Filter with plug and play features. IEEE Transactions on Control of Network Systems. Volume 5 (1),
2018, pp 560-570.
[38]
S. Raimondi Cominesi, M. Farina, L. Giulioni, B. Picasso, R.
Scattolini. A two-layer stochastic Model
Predictive Control scheme for microgrids. IEEE
Transactions on Control Systems Technology, Volume 26 (1), pp. 1-13, 2018.
[39]
M. Farina, L. Giulioni, R. Scattolini. Stochastic linear Model Predictive Control with chance
constraints - a review. Journal of process control, Volume 44, pp.
53-67, 2016.
[40]
M. Farina, R. Scattolini. Model
predictive control of linear systems with multiplicative unbounded uncertainty and
chance constraints. Automatica, Volume 70, pp. 258-265, 2016.
[41] M. Farina, G.
P. Ferrari, F. Manenti, E. Pizzi. Assessment
and comparison of distributed model predictive control schemes: application to
a natural gas refrigeration plant. Computers
& Chemical Engineering, Volume 89, pp. 192-203, 2016.
[42]
A. Perizzato, M. Farina, R. Scattolini. Application of distributed predictive control to
motion and coordination problems for unicycle autonomous robots. Robotics and autonomous systems. Volume 72,
pp. 248-260, 2015.
[43]
S. Riverso, M. Farina, G. Ferrari Trecate. Plug-and-play state estimation and application to
distributed output-feedback model predictive control. European Journal of Control, Volume 25, pp. 17-26, 2015.
[44]
M. Farina, L. Giulioni, L. Magni, R. Scattolini. An MPC approach to output-feedback control of
stochastic linear discrete-time systems. Automatica. Volume 55,
pp. 140-149, 2015.
[45]
M. Farina, E. Osto, A. Perizzato, L. Piroddi, R. Scattolini. Fault Detection and Isolation of Bearings in a Drive
Reducer of a Hot Steel Rolling Mill. Control
Engineering Practice, Volume 39, 2015, pp. 35-44.
[46]
M. Farina, A. Guagliardi, F. Mariani, C. Sandroni, R.
Scattolini. Model predictive control of voltage
profiles in MV networks with distributed generation. Control Engineering Practice. Volume 34,
January 2015, pp. 18-29, 2015.
[47]
M. Farina, G. Betti, R. Scattolini. Distributed Predictive Control of continuous-time systems. Systems and
Control Letters. Volume 74, pp. 32-40, 2014.
[48]
S. Riverso, M. Farina, G. Ferrari Trecate. Plug-and-play model predictive control based on robust
control invariant sets. Automatica. Volume 50, Issue 8, pp. 2179-2186, 2014
[49]
G. Betti, M. Farina, R. Scattolini. Realization issues, tuning, and testing of a distributed predictive
control algorithm. Journal of Process Control. Volume 24, Issue 4, pp.
424-434, 2014.
[50]
M. Farina, L. Giulioni, G. Betti, and R. Scattolini. An approach to distributed predictive control for
tracking - theory and applications. IEEE Transactions on Control System Technology. Volume 22,
Issue 4, 2014, pp. 1558-1566.
[51] M. Farina, P.
Colaneri, and R. Scattolini. Block-wise discretization accounting
for structural constraints. Automatica, Volume 49,
2013, pp. 3411-3417.
[52]
S. Aghaei, F. Sheikholeslam, M. Farina, and R. Scattolini. An MPC-based reference governor approach for
offset-free control of constrained linear systems. International
Journal of Control. Volume 86, number 9, 2013, pp. 1534-1539.
[53]
G. Betti, M. Farina, and R. Scattolini. A robust MPC algorithm for offset-free tracking of
constant reference signals. IEEE Transactions on Automatic Control. Volume 58,
number 9, 2013, pp. 2394-2400.
[54]
S. Riverso, M. Farina, and G. Ferrari Trecate. Plug-and-Play Decentralized Model Predictive Control
for Linear Systems. IEEE Transactions on Automatic Control. Volume 58, number 10,
2013, pp. 2608-2614.
[55]
G. Betti, M. Farina, G. A. Guagliardi, A. Marzorati, and R.
Scattolini. Development of a Control-Oriented
Model of Floating Wind Turbines. IEEE Transactions on Control System Technology. Volume 22,
Issue 1, 2014, pp. 69-82.
[56]
L. Piroddi, M. Farina and M. Lovera. Black Black box model identification of
nonlinear input-output models: a Wiener-Hammerstein
benchmark. Control Engineering Practice (2012), vol. 20, p. 1109-1118.
[57]
M. Farina and R. Scattolini. Tube-based robust sampled-data MPC for linear continuous-time systems. Automatica 48, 2012, pp.
1473-1476.
[58]
M. Farina and R. Scattolini. Distributed predictive control: a non-cooperative algorithm with
neighbor-to-neighbor communication for linear systems. Automatica 48, pp. 1088 - 1096.
[59]
M. Giroletti, M. Farina and R. Scattolini. A hybrid frequency/power based
method for industrial load shedding. International
Journal of Electrical Power and Energy Systems, 35 (2012), pp 194-200.
[60]
P. S. Carinci, M. Farina, F. Manenti, R. Scattolini. Application of advanced estimation techniques to a
chemical plant model. \emph{Chemical Engineering
Transactions}. Volume 29, 2012, pp. 1609 - 1614.
[61] E. Sacco, M. Farina, C. Greco, S. s
a system-level property generated by its multi-domain structure. Biotechnology Advances, Special Issue IBS2010, Systems
Biology, 2012 30(1), pp. 154-168.
[62]
M. Farina, G. Ferrari-Trecate and R. Scattolini. Distributed moving horizon estimation for nonlinear
constrained systems. International
Journal of Nonlinear and Robust Control, Volume 22 (2012), pp. 123-143.
[63]
R. Chignola, V. Vyshemirsky, M. Farina, A. Del Fabbro, E.
Milotti. Modular model of TNFα
cytotoxicity. Bioinformatics 2011,
27, pp 1754-1757.
[64]
R. Chignola, A. Del Fabbro, M. Farina and E. Milotti. Computational challenges of tumor spheroid modeling. Journal of Bioinformatics and Computational Biology 9(4), pp.
559-577.
[65]
M. Farina, G. Ferrari-Trecate, Carlo Romani and R.
Scattolini. Moving horizon estimation for
distributed nonlinear systems with application to cascade river reaches. Journal of Process Control, 21 (2011). pp. 767-774.
[66]
M. Farina, L. Piroddi. Simulation
error minimization identification method based on multi-stage prediction. International
Journal of Adaptive Control and Signal Processing, 25 (2011), pp.. 389-406.
[67]
M. Farina, L. Piroddi. Identification
of Polynomial Input/Output Recursive Models with Simulation Error Minimization
Methods. International Journal of System Science, 43 (2012), pp.. 319-333.
[68]
M. Farina, L. Piroddi. An iterative
algorithm for simulation error based identification of
polynomial input-output models using multi-step prediction. International Journal of Control, Volume
83 (7), July 2010, pp. 1442-1456.
[69]
M. Farina, L. Galleani, P. Tavella, S. Bittanti. A control theory approach to clock steering
techniques. IEEE Transactions on Ultrasonics,
Ferroelectrics and Frequency Control. , vol. 57,
no. 10, October 2010, pp. 2257 - 2270.
[70]
M. Farina, G. Ferrari-Trecate and R. Scattolini. Moving-horizon partition-based state estimation of
large-scale systems. Automatica. Volume
46(5), 2010. pp.. 910-918.
[71] M. Farina, G.
Ferrari-Trecate and R. Scattolini. Distributed
Moving Horizon Estimation for Linear Constrained Systems. IEEE Transactions on Automatic Control. Volume 55
(11), pp. 2462-2475.
[72]
E. Pisoni, M. Farina, C. Carnevale, L. Piroddi. Forecasting peak air pollution levels using NARX
models. Engineering Applications of Artificial Intelligence, 22 (4-5),
2009. pp. 593-602.
[73]
M. Farina, S. Bittanti. An observer
for mass-action chemical reaction networks. European Journal of Control,
Volume 15 (5), 2009. pp. 578--593.
[74]
M. Farina, S. Bittanti, P. Tavella, L. Galleani. Control of clock signals. Journal of the Franklin
Institute, 346(5), 2009. pp. 449-469.
[75]
E. Bullinger, D. Fey, M. Farina, R.
Findeisen. Identifikation biochemischer Reaktionsnetzwerke: ein
beobachterbasierter Ansatz. Identification of biochemical reaction networks: an
observer based approach. AT - Automatisierungstechnik, DE 56
(2008) 5. pp. 269-279.
[76]
E. Milotti, R. Chignola, C. Dalla Pellegrina, A. Del Fabbro,
M. Farina, D. Liberati. VBL: Virtual Biophysics Lab. Il nuovo cimento C,
31(1). pp. 109-118, 2008.
[1] S. Chourasiya, L. Bascetta, M. Farina, G. Ferretti. Feedback linearization of
a single-track dynamic model with steering actuator delay. Accepted at ECC2025 conference.
[2] L. Boca de Giuli, A. La
Bella, M. Farina, R. Scattolini. Modeling and
predictive control of networked systems via physics-informed neural networks. 2024 IEEE 63rd Conference on Decision and
Control (CDC), Milan, Italy, pp. 3005-3010, 2024.
[3] J. Li, M. Corno, M. Farina.
A method to detect the sudden stopping in an assistive robot for the visually
impaired people. 2024 Modeling,
Estimation and Control Conference (MECC 2024), IFAC-PapersOnLine,
Volume 58, Issue 28, pp. 624-629, 2024.
[4] W. D'Amico, S. Zanini, A. La
Bella, M. Farina. LMI-based control design with robust local stability
guarantees for linear discrete-time systems with input saturations. 2024 European Control Conference (ECC),
Stockholm, Sweden, pp. 3490-3495, 2024.
[5] F. Bonassi, A. La Bella, G. Panzani, M. Farina, R. Scattolini.
Deep Long-Short Term Memory networks: Stability properties and Experimental
validation. 2023 European Control
Conference (ECC), Bucharest, Romania, pp. 1-6, 2023.
[6] M. Farina, P. Rattamasanaprapai,
P. Marson, F. Camuncoli, M. Galli. Design,
realization, control, and validation of a smart tether system for a robotic
guide for blind and visually impaired users. 2023 IFAC World Congress, IFAC-PapersOnLine,
Volume 56, Issue 2, pp. 1115-1120, 2023.
[7] W. D'Amico, A. La Bella, M. Farina. Data-based control
design for nonlinear systems with recurrent neural network-based controllers. 2023 IFAC World Congress, IFAC-PapersOnLine, Volume 56, Issue 2, Pages 6235-6240,
2023.
[8]
W. D'Amico, M. Farina. Data-based control design for linear discrete-time systems with robust
stability guarantees. CDC22 Conference, pp. 1429-1434, 2022.
[9]
F. Bonassi, J. Xie, M. Farina, R. Scattolini. An Offset-Free Nonlinear MPC scheme for systems
learned by Neural NARX models. CDC2022
Conference, pp. 2123-2128, 2022.
[10] F. Bonassi, J. Xie, M. Farina, R. Scattolini.
Towards lifelong learning of
Recurrent Neural Networks for control design. ECC2022 Conference, pp.
2018-2023, 2022.
[11] W. D'Amico, M.
Farina, G. Panzani. Recurrent Neural Networks controllers
learned using Virtual Reference Feedback Tuning with application to an
Electronic Throttle Body. ECC2022 Conference, pp. 2137-2142, 2022.
[12] F. Bonassi, M.
Farina, R. Scattolini. Stability of discrete-time
feed-forward neural networks in NARX configuration. SYSID 2021, recipient of the Young Author Award.
[13] E. Terzi, T.
Bonetti, D. Saccani, M. Farina, L. Fagiano, R. Scattolini. Data-driven predictive control of the cooling system
of a large business center. 24th
International Symposium on Mathematical Theory of Networks and Systems (MTNS
2020).
[14] L. Bugliari
Armenio, L. Fagiano, E. Terzi, M. Farina, and R. Scattolini. Optimal Training of Echo State Networks via Scenario
Optimization, IFAC-PapersOnLine,
Volume 53, Issue 2, pp. 5183-5188, 2020.
[15] F. Petzke, M.
Farina, S. Streif. A Hierarchical MPC Scheme for
Ensembles of Hammerstein Systems, IFAC-PapersOnLine, Volume 53, Issue 2, pp. 6951-6956, 2020.
[16] S. Spinelli,
E. Longoni, M. Farina, F. Petzke, S. Streif, A. Ballarino. A Hierarchical Architecture for the Coordination of an
Ensemble of Steam Generators, IFAC-PapersOnLine, Volume 53, Issue 2, pp. 11557-11562, 2020
[17] L. Xu, B. Guo,
C. L. Galimberti, M. Farina, R. Carli, G. Ferrari-Trecate. Suboptimal Distributed LQR Design for Physically
Coupled Systems. IFAC-PapersOnLine,
Volume 53, Issue 2, pp. 11032-11037, 2020.
[18] F. Bonassi, E.
Terzi, M. Farina and R. Scattolini. LSTM
Neural Networks: Input to State Stability and Probabilistic Safety
Verification. Proceedings of the 2nd
Conference on Learning for Dynamics and Control, pp. 85-94, 2020.
[19] J. R.
Salvador, E. Terzi, M. Farina, D. R. Ramirez, D. Munoz de la Pena, R.
Scattolini. Learning-based predictive control for
MIMO systems. 2019 IEEE 58th Conference
on Decision and Control (CDC), 2019, pp. 7671-7676.
[20] A. La Bella,
F. Bonassi, M. Farina, R. Scattolini. Two-layer
model predictive control of systems with independent dynamics and shared
control resources. Proceedings of LSS
2019, IFAC PapersOnLine 52-3, pp. 96-101.
[21] L. Bugliari
Armenio, E. Terzi, M. Farina, R. Scattolini. Echo State Networks: analysis, training and predictive control. Proceedings of ECC, 2019, pp. 799-804.
[22]
S. Spinelli, M. Farina and A. Ballarino. An optimal control of start-up for nonlinear re-tube
boilers with thermal stress constraints. Proceedings
of ECC 2019, pp. 2362-2367.
[23] E. Rossi, M.
Bruschetta, R. Carli, Y. Chen, M. Farina. Online Nonlinear Model Predictive Control for tethered UAVs to perform a
safe and constrained maneuver. Proceedings
of ECC 2019, pp. 3996-4001.
[24] F. Petzke, M.
Farina, S. Streif. A Multirate
Hierarchical MPC Scheme for Ensemble Systems. Proceedings of CDC 2018, pp. 5874-5879.
[25] P. Mc Namara, R. Negenborn, J. C. Canizares, M.
Farina, J. M. Maestre, P. Trodden, S. Olaru. Life
lessons from and for distributed MPC, Part 1: Dynamics of cooperation. Proceedings of the IFAC Conference on
Technology, Culture and International Stability - 18th TECIS 2018. IFAC PapersOnLine 51-30, pp. 101-106.
[26]
P. Mc Namara,
R. Negenborn, J. C. Canizares,
M. Farina, J. M. Maestre, P. Trodden, S. Olaru. Life
lessons from and for distributed MPC, Part 2: Choice of decision makers. Proceedings of the IFAC Conference on
Technology, Culture and International Stability - 18th TECIS 2018. IFAC PapersOnLine 51-30, pp. 101-106.
[27] A. La Bella,
M. Farina, C. Sandroni, R. Scattolini. On the design of a microgrids aggregation management framework to
provide ancillary services. Proceedings
of the CIRED Workshop, 2018, paper 497.
[28] E. Terzi, L.
Fagiano, M. Farina, R. Scattolini. Identification
of the cooling system of a large business center. 18th IFAC Symposium on System Identification, pp. 174-179.
[29]
S. Attuati, M. Farina, F. Boem and T. Parisini. Reducing false alarm rates in observer-based
distributed fault detection schemes by analysing
moving averages. Proceedings of
SAFEPROCESS 2018. IFAC PapersOnLine 51 24, pp. 473-479.
[30]
A. La Bella, M. Farina, C. Sandroni, R. Scattolini. Microgrids aggregation management providing ancillary
services. Proceedings of the European
Control Conference, 2018, pp. 1136-1141.
[31]
E. Terzi, L. Fagiano, M. Farina, R. Scattolini. Learning multi-step prediction models for receding
horizon control. Proceedings of
the European Control Conference, 2018, pp. 1335-1340.
[32] E. Terzi, M.
Farina, L. Fagiano, R. Scattolini. Robust
predictive control with data-based multi-step prediction models. Proceedings of the European Control
Conference, 2018, pp. 1710-1715.
[33] S. Spinelli,
M. Farina and A. Ballarino. A hierarchical optimization-based
scheme for combined Fire-tube Boiler/CHP generation units. Proceedings of the European Control Conference, 2018, pp. 416-421.
[34] M. Lauricella,
M. Farina, R. Schneider, R. Scattolini. A distributed fault detection and isolation algorithm based on Moving
Horizon Estimation. IFAC WC 2017, pp.
15259 15264, 2017.
[35]
M. Farina, X. Zhang, R. Scattolini. A hierarchical MPC scheme for interconnected systems. IFAC WC 2017, pp. 12021-12026.
[36] E. Ceravolo,
M. Gabellone, M. Farina, L. Bascetta, M. Matteucci. Model Predictive Control of an autonomous wheelchair. IFAC WC 2017, pp. 9821- 9826.
[37] S. Raimondi
Cominesi, A. La Bella, M. Farina, R. Scattolini. A multi-layer control scheme for microgrid energy management. IFAC
Workshop on Control of Transmission and Distribution Smart Grids, CTDSG 2016, pp. 256-261.
[38] F. Boem, R.
Carli, M. Farina, G. Ferrari-Trecate, T. Parisini. Scalable Monitoring of Interconnected Stochastic Systems. Proceedings of CDC 2016: 1285-1290.
[39] M. Farina, L.
Giulioni, R. Scattolini. Distributed Predictive Control of
Stochastic Linear Systems with chance constraints. Proceedings of ACC 2016, pp. 20-25.
[40] M. Farina, R. Carli. Distributed state estimation for
independent linear systems with relative and absolute measurements. Proceedings of ACC 2016, pp. 2029-2034.
[41] M. Farina, R. Carli. Plug and play partition-based
state estimation based on Kalman flter. 2015 IEEE Conference on Decision and Control,
pp. 3155 - 3160.
[42] A. Perizzato,
M. Farina, R. Scattolini. Formation control and collision
avoidance of unicycle robots with distributed predictive control. 5th IFAC Conference on Nonlinear Model
Predictive Control 2015 (NMPC'15), Volume 48, Issue 23, pp. 260-265.
[43] M. Farina, R. Scattolini.
Model predictive control of linear systems with multiplicative unbounded
uncertainty and average constraints. 5th
IFAC Conference on Nonlinear Model Predictive Control 2015 (NMPC'15),
Volume 48, Issue 23, pp. 266-271.
[44]
S. Raimondi Cominesi, M. Farina, L. Giulioni, B. Picasso, and
R. Scattolini. Two-layer predictive control of a
micro-grid including stochastic energy sources. American
Control Conference 2015, pp. 918-923.
[45] A. Perizzato,
M. Farina, R. Scattolini. Stochastic Distributed Predictive
Control of Independent Systems with Coupling Constraints. 2014 IEEE Conference on Decision and Control, pp. 3228 - 3233.
[46] A. Perizzato,
M. Farina, L. Piroddi, R. Scattolini, E. Osto. Fault Detection of Bearings in a Drive Reducer of a Hot Steel Rolling
Mill. 2014 IEEE Multi-conference on
Systems and Control, pp. 77-82.
[47] M. Farina, L.
Giulioni, L. Magni, and R. Scattolini. Output Feedback Model Predictive Control: a probabilistic approach. IFAC World Congress 2014, Volume 19,
Part 1, pp. 7461-7466.
[48]
M. Farina, D. Zoni, W. Fornaciari. A control-inspired iterative algorithm for memory management in NUMA multicores.
IFAC World Congress 2014, pp. 6117-6122.
[49]
S. Riverso, M. Farina, G. Ferrari Trecate. Design of plug-and-play model predictive control: an
approach based on linear programming. CDC
2013 Conference, pp. 6530 - 6535.
[50]
S. Riverso, M. Farina, R. Scattolini, G. Ferrari Trecate. Plug-and-play distributed state estimation for linear
systems. CDC 2013 Conference, pp. 4889 -
4894.
[51]
G. Betti, M. Farina, and R. Scattolini. Decentralized predictive control for tracking constant
references. CDC 2013
Conference, pp. 5228 - 5233.
[52] M. Farina, L.
Giulioni, L. Magni, and R. Scattolini. A probabilistic approach to model predictive control. CDC 2013 Conference, pp. 7734 - 7739.
[53] M. Farina, G.
Betti, R. Scattolini. A solution to the tracking problem
using distributed predictive control. Proceedings
of the ECC 2013 Conference, pp. 4347 - 4352.
[54]
G. Betti, M. Farina, and R. Scattolini. An MPC algorithm for o set-free tracking of constant
reference signals. IEEE CDC 2012
Conference, pp. 5182 - 5187.
[55]
S. Riverso, M. Farina, and G. Ferrari-Trecate. Plug and play decentralized model predictive control. IEEE CDC 2012 Conference, pp. 4193-4198.
[56] G. Betti, M.
Farina, A. Marzorati, R. Scattolini, and G. A. Guagliardi. Modeling and control of a oating
wind turbine with spar buoy platform. IEEE
International Energy Conference and Exhibition (ENERGYCON), 2012, pp.
189-194.
[57]
G. Betti, M. Farina, and R. Scattolini. Distributed predictive control for tracking constant
references. 2012 American
Control Conference, pp. 6364 - 6369.
[58] P. Colaneri,
M. Farina, R. Scattolini, R. Shorten. A note on
discretization of sparse linear systems. Proceedings
of the 7th IFAC Symposium on Robust Control Design, (ROCOND'12), pp. 97 -
102.
[59] M. Farina, R. Scattolini. An
output feedback distributed predictive control algorithm. 50th IEEE Conference on Decision and Control,
Orlando, Florida, USA 2011, December 12-15 2011, pp. 8139-8144.
[60] M. Farina, R. Scattolini.
Distributed non-cooperative MPC with neighbor-to-neighbor communication. Proceedings of the IFAC 2011 World
Conference. August 28 - September 2 2011, Milan, Italy. pp. 404 - 409.
[61] F. Casella, M.
Farina, F. Righetti, R. Scattolini, D. Faille, F. Davelaar, A. Tica, H.
Gueguen, D. Dumur. An optimization procedure of the
start-up of Combined-Cycle Power Plants. Proceedings
of the IFAC 2011 World Conference. August 28 - September 2 2011, Milan,
Italy. pp. 7043 - 7048.
[62] E. Pisoni, M.
Farina, G. Pagani, L. Piroddi. Environmental Over-Threshold Event
Forecasting using NARX Models. Proceedings
of the IFAC 2011 World Conference. August 28 - September 2 2011, Milan,
Italy. pp. 10559 - 10564.
[63]
M. Farina, L. Piroddi.
Convergence properties of an iterative prediction approach to nonlinear SEM
parameter estimation. Proceedings of the
49th IEEE Conference on Decision and Control. December
15-17, 2010, Atlanta, GA, USA. pp. 7226 - 7231.
[64] M. Farina, G.
Ferrari-Trecate and R. Scattolini. Distributed
moving horizon estimation for nonlinear constrained systems. Proceedings of the NOLCOS 2010 conference,
2010. pp. 909 - 914.
[65] M. Farina, G.
Ferrari-Trecate and R. Scattolini. State
estimation for large-scale partitioned systems: a moving horizon approach. Proceedings of the 2010 American Control
Conference, Baltimore, MD, USA, June 30-July 2, 2010. pp. 3180-3185.
[66] M. Farina and
L. Piroddi. Approximate SEM identification of
polynomial input-output models. Proceedings
of the 2010 American Control Conference, Baltimore, MD, USA, June 30-July
2, 2010. pp. 7040-7045.
[67] M. Farina, G.
Ferrari-Trecate and R. Scattolini. A moving
horizon scheme for distributed state estimation. Proceedings of the 48th Conference on Decision and Control, CDC 2009,
Shangai, China 16-18 December 2009. pp. 1818-1823.
[68] M. Farina, G.
Ferrari-Trecate and R. Scattolini. Distributed
moving horizon estimation for sensor networks. Proceedings of the 1st IFAC Workshop on Estimation and Control of
Networked Systems, pp. 126-131, Venice, Italy, September 24-26, 2009.
[69] M. Farina, L. Piroddi.
Simulation Error Minimization-Based Identification of Polynomial Input-Output
Recursive Models. 15th IFAC Symposium on
System Identification, pp. 1393-1398, Saint-Malo (France), July 6-8, 2009.
[70] L. Piroddi, M.
Farina, M. Lovera. Polynomial NARX Model Identification:
a Wiener-Hammerstein Benchmark. 15th IFAC Symposium on System Identification, pp. 1074-1079,
Saint-Malo (France), July 6-8, 2009.
[71] M. Farina, L. Piroddi. Some
Convergence Properties of Multi-Step Prediction Error Identification Criteria. Proceedings of the 47th Conference on
Decision and Control, Cancun, Mexico 9-11 Dicembre
2008. pp. 756-761.
[72] M. Farina, R. Findeisen, E.
Bullinger, S. Bittanti, F.Allgoewer, P. Wellstead.
Results towards identifiability properties of biochemical reaction networks. Proceedings of the 45th Conference on
Decision and Control San Diego, CA, USA 13-15 Dicember
2006. pp. 2104-2109.
[73] S. Bittanti,
A. De Marco, M. Farina, S. Spelta. Modelling
and simulation of a Dish Stirling solar engine. Proceedings of the 16th IFAC World Conference, Praha, Czech
Republic, 3-8 July 2005, pp. 362-367.
[1]
M. Farina, M. Prandini. Hybrid models for gene regulatory networks: The
case of lac operon in E.Coli. Hybrid Systems: Computation and Control, Bemporad,
Alberto; Bicchi, Antonio; Buttazzo,
Giorgio (Eds.), Lecture Notes in Computer Science, Springer-Verlag, ISBN:
978-3-540-71492-7, pp 693-697.
[2]
G. Betti, M.
Farina, and R. Scattolini. Distributed predictive control: a noncooperative approach based on
robustness concepts. Intelligent Systems,
Control and Automation: Science and Engineering, Vol. 69, Springer, 2013,
ISBN 978-94-007-7005-8, Chapter 25.
[3]
P. Colaneri, M. Farina, S.
Kirkland, R. Scattolini, R. Shorten. Positive Systems: Discretization with Positivity and
Constraints. Hybrid systems with constraints. J. Daafouz, S. Tarbouriech, and M. Sigalotti
(Eds.). Automation, control and industrial engineering series. iSTE - WILEY, 2013, ISBN: 978-1-84821-527-6, Chapter 1.
[4]
M. Farina, G. Ferrari-Trecate, C.
Jones, S. Riverso and M. Zeilinger. Scalable MPC Design. Handbook of Model Predictive Control. Birkhauser, Control
Engineering, Sasa V. Rakovic and William S. Levine Editors, pp. 259-286.
[5]
M. Farina, R. Scattolini. Distributed MPC for large-scale systems. Handbook of Model Predictive Control.
Birkhauser, Control Engineering, Sasa V. Rakovic and William S. Levine Editors,
pp. 239-258.
[1]
M. Farina. Observer design and parameter identification for
mass-action biochemical reaction networks. Supervisor: Prof. S. Bittanti. PhD Thesis, Politecnico
di Milano, 2007.
[2]
M. Farina. Il motore solare Dish Stirling: modellistica e controllo. Relatore: Prof. S. Bittanti. Tesi di Laurea,
Politecnico di Milano, Giugno 2003.