[ALVL18] N. Ahmed, M. Levorato, R. Valentini and G.P. Li, ``Residential Demand Response: Optimization of Generation, Storage and Load Management'', in IEEE SmartgridComm, Under Review.
[BPDB18] A. Borri, G. Pola and M.D. Di Benedetto, Design of Symbolic Controllers for Networked Control Systems, IEEE Transactions on Automatic Control, full paper, (in press, print May 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, accepted for publication in Proc. of the 2nd URSI AT-RASC, Gran Canaria, 28, May 1 June 2018.
[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, submitted 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, accepted for publication in 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, submitted to 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, In Press,
[IDDD2018] A. Iovine, T. Rigaut, G. Damm, E. De Santis, M.D. Di Benedetto, Power Management for an DC MicroGrid integrating Renewables and Storages, 2018 (submitted).
[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.
[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, submitted to IEEE Transactions on Communications.
[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.