[BPDB19] A. Borri, G. Pola and M.D. Di Benedetto, Design of Symbolic Controllers for Networked Control Systems, IEEE Transactions on Automatic Control, full paper, VOL. 64, NO. 3, MARCH 2019
[IDDD2019] A. Iovine, T. Rigaut, G. Damm, E. De Santis, M.D. Di Benedetto, Power Management for an DC MicroGrid integrating Renewables and Storages, Control Engineering Practice, Volume 85, April 2019, Pages 59-79
[PMDB19] G. Pola, C. Manes and M.D. Di Benedetto, Output Feedback Control via Bisimulation of Stochastic Linear Systems, IEEE Control Systems Letters, 3(1): 25-30, January 2019.
[CPV+18] S. Chiocchio, A. Persia, F. Valentini, E. Cinque, M. Pratesi, F. Santucci, Integrated Simulation Environments for Vehicular Communications in Cooperative Road Transportation Systems, Proc. of the 2nd URSI AT-RASC, Gran Canaria, 28, May 1 June 2018. DOI: 10.23919/URSI-AT-RASC.2018.8471321
[CCP+18] S. Chiocchio, E. Cinque, A. Persia, P. Salvatori, C. Stallo, M. Salvitti, F. Valentini, M. Pratesi, F. Rispoli, A. Neri, F. Santucci, A Cooperative Framework for Next Generation of Intelligent Transportation Vehicles, to IEEE International Forum on Research and Technologies for Society and Industry (RTSI), Palermo, Italy, September 2018.
[CVP+18b] E. Cinque, F. Valentini, M. Pratesi, S. Chiocchio and A. Persia, Analysis and experimental characterization of channel congestion control in vehicular networks, Proc. of the International Symposium on Networks, Computers and Communications (ISNCC), Rome, 2018.
[CWLP18] E. Cinque, H. Wymeersch, C. Lindberg and M. Pratesi, Toward a Standard- Compliant Implementation for Consensus Algorithms in Vehicular Networks, IEEE Connected and Automated Vehicles Symposium 2018, Chicago 2018.
[FFB+18] M. Fakhroleslam, S. Fatemi, R.B. Boozarjomehry, E. De Santis, M.D. Di Benedetto, G. Pola, Maximal Safe Set Computation for Pressure Swing Adsorption Processes Computers & Chemical Engineering, vol. 109, pp. 179-190, 2018
[FBB+18] M. Fakhroleslam, R. B. Boozarjomehry, S. Fatemi, E. De Santis, M.D. Di Benedetto, G. Pola, Design of a Hybrid Controller for Pressure Swing Adsorption Processes. IEEE Transactions on Control Systems Technology, p. 1-15, ISSN: 1063-6536, doi: 10.1109/TCST.2018.2841384
[FDS+18] G. Fiore, E. De Santis, M.D. Di Benedetto, Predictability for Finite State Machines. A set-membership approach, 14th Workshop on Discrete Event Systems, 2018, IFAC- PapersOnLine Volume 51, Issue 7, 2018, Pages 355-360.
[FDSDB2018] G. Fiore, E. De Santis and M.D. Di Benedetto, Secure Diagnosability of Hybrid Dynamical Systems, in Sayed-Mouchaweh, Moamar (Ed.), Diagnosability, Security and Safety of Hybrid Dynamic and Cyber-Physical Systems, Springer International Publishing, pp. 175- 200, 2018.
[FDS+18] G. Fiore, E. De Santis, G. Pola and M.D. Di Benedetto, On approximate predictability of metric systems6th IFAC Conference on Analysis and Design of Hybrid Systems, IFAC-PapersOnLine Volume 51, Issue 16, 2018, Pages 169-174
[PPDB18a] P. Pepe, G. Pola and M.D. Di Benedetto, On Lyapunov–Krasovskii Characterizations of Stability Notions for Discrete-Time Systems with Uncertain Time- Varying Time-Delays, IEEE Transactions on Automatic Control, 63(6): 1603-1617, June 2018.
[PPDB18b] G. Pola, P. Pepe and M.D. Di Benedetto, Decentralized Approximate Supervisory Control of Networks of Nonlinear Control Systems, IEEE Transactions on Automatic Control, 63(9):2803-2817, September 2018.
[PMVdS+18] G. Pola, C. Manes, A.J. van der Schaft and M.D. Di Benedetto, Equivalence notions for discrete-time stochastic linear control systems, IEEE Transactions on Automatic Control, 63(7):1897-1912, July 2018.
[PDSDB18] G. Pola, E. De Santis and M.D. Di Benedetto, Approximate Diagnosis of Metric Systems, IEEE Control Systems Letters 2(1): 115-120, January 2018.
[VLS18] R. Valentini, M. Levorato and F. Santucci, Optimal Aging-aware Channel Access and Power Allocation for Battery–Powered Devices with Radio Frequency Energy Harvesting, IEEE Transactions on Communications, Volume: 66 , Issue: 11 , Nov. 2018, pp. 5773 - 5787
[JSBM18] A. Jain, F. Smarra, M. Behl, R. Mangharam, Data-Driven Model Predictive Control with Regression Trees - An Application to Building Energy Management, ACM Transactions on Cyber-Physical Systems, 2(1), 2018.
[SJDD+18] F. Smarra, A. Jain, T. de Rubeis, D. Ambrosini, A. D’Innocenzo, R. Mangharam, Data-driven model predictive control using random forests for building energy optimization and climate control, Applied Energy, 226: 1252-1272, 2018.
[SJMD+18] F. Smarra, A. Jain, R. Mangharam, A. D’Innocenzo. Data-driven Switched Affine Modeling for Model Predictive Control, ADHS 2018, Oxford, UK, July 11-13, 2018.