Advanced control methods and stability analysis [3, 5, 7, 1, 2, 18, 4, 9, 8]
Automotive systems [10, 11, 15, 12, 13, 14, 16, 21, 47, 54]
Water and energy grids, and renewable energy sources [22, 23, 26, 29, 35, 37, 40, 46, 45, 52, 53, 25, 28, 30, 31, 32, 55]
Biomedical applications and systems biology [17, 20, 24, 27, 33]
Emerging topics and learning-based control and decision [36, 43, 44, 48, 50, 51]
Networked and Boolean control systems [34, 38, 39, 41, 42, 49]
[1] M. Corless and L. Glielmo. “On the exponential stability of singularly perturbed systems”. In: SIAM Journal on Control and Optimization 30.6 (1992), pp. 1338–1360.
[2] M. Corless, F. Garofalo, and L. Glielmo. “New results on composite control of singularly perturbed uncertain linear systems”. In: Automatica 29.2 (1993), pp. 387–400. doi: 10.1016/0005-1098(93)90131-C.
[3] F. Garofalo, G. Celentano, and L. Glielmo. “Stability Robustness of Interval Matrices Via Lyapunov Quadratic Forms”. In: IEEE Transactions on Automatic Control 38.2 (1993), pp. 281–284. doi: 10.1109/9.250472.
[4] L. Glielmo, P. Marino, R. Setola, and F. Vasca. “Reduced Kalman filtering for indirect adaptive control of the induction motor”. In: International Journal of Adaptive Control and Signal Processing 8.6 (1994), pp. 527–541. doi: 10.1002/acs.4480080602.7
[5] F. Amato, F. Garofalo, L. Glielmo, and A. Pironti. “Robust and quadratic stability via polytopic set covering”. In: International Journal of Robust and Nonlinear Control 5.8 (1995), pp. 745–756. doi: 10.1002/rnc.4590050806.
[7] M. Corless and L. Glielmo. “New converse Lyapunov theorems and related results on exponential stability”. In: Mathematics of Control, Signals, and Systems 11.1 (1997), pp. 79–100. doi: 10.1007/bf02741886.
[8] M. di Bernardo, F. Garofalo, L. Glielmo, and F. Vasca. “Switchings, bifurcations, and chaos in DC/DC converters”. In: IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 45.2 (1998), pp. 133–141. doi: 10.1109/81.661675.
[9] L. Glielmo, R. Setola, and F. Vasca. “An interlaced extended Kalman filter”. In: IEEE Transactions on Automatic Control 44.8 (1999), pp. 1546–1549. doi: 10 .1109/9.780418.
[10] G. Fiengo, L. Glielmo, and S. Santini. “On-board diagnosis for three-way catalytic converters”. In: International Journal of Robust and Nonlinear Control 11.11 (2001), pp. 1073–1094. doi: 10.1002/rnc.645.
[11] L. Glielmo and S. Santini. “A two-time-scale infinite-adsorption model of three way catalytic converters during the warm-up phase”. In: Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME 123.1 (2001), pp. 62–70. doi: 10.1115/1.1345529.
[12] O. Barbarisi, F. Vasca, and L. Glielmo. “State of charge Kalman filter estimator for automotive batteries”. In: Control Engineering Practice 14.3 SPEC. ISS. (2006), pp. 267–275. doi: 10.1016/j.conengprac.2005.03.027.
[13] L. Glielmo, L. Iannelli, V. Vacca, and F. Vasca. “Gearshift control for automated manual transmissions”. In: IEEE/ASME Transactions on Mechatronics 11.1 (2006), pp. 17–26. doi: 10.1109/TMECH.2005.863369.
[14] G. Fiengo, L. Glielmo, and F. Vasca. “Control of auxiliary power unit for hybrid electric vehicles”. In: IEEE Transactions on Control Systems Technology 15.6 (2007), pp. 1122–1130. doi: 10.1109/TCST.2006.890301.
[15] G. Fiengo, S. Santini, and L. Glielmo. “Emission reduction during TWC warm-up: Control synthesis and hardware-in-the-loop verification”. In: International Journal of Modelling, Identification and Control 3.3 (2008), pp. 233–246. doi: 10.1504/IJMIC.2008.020122.
[16] A. di Gaeta, L. Glielmo, V. Giglio, and G. Police. “Modeling of an electrome chanical engine valve actuator based on a hybrid analytical - FEM approach”. In: IEEE/ASME Transactions on Mechatronics 13.6 (2008), pp. 625–637. doi: 10.1109/TMECH.2008.2003469.
[17] S. Santaniello, G. Fiengo, L. Glielmo, and G. Catapano. “A biophysically inspired microelectrode recording-based model for the subthalamic nucleus activity in Parkinson’s disease”. In: Biomedical Signal Processing and Control 3.3 (2008), pp. 203–211. doi: 10.1016/j.bspc.2008.03.001.
[18] L. Glielmo and M. Corless. “On output feedback control of singularly perturbed systems”. In: Applied Mathematics and Computation 217.3 (2010), pp. 1053–1070. doi: 10.1016/j.amc.2010.02.035.8
[20] S. Santaniello, G. Fiengo, L. Glielmo, and W. M. Grill. “Closed-loop control of deep brain stimulation: A simulation study”. In: IEEE Transactions on Neural Systems and Rehabilitation Engineering 19.1 (2011), pp. 15–24. doi: 10.1109/TNSRE.2010.2081377.
[21] G. Palmieri, M. Barić, L. Glielmo, and F. Borrelli. “Robust vehicle lateral stabilisation via set-based methods for uncertain piecewise affine systems”. In: Vehicle System Dynamics 50.6 (2012), pp. 861–882. doi: 10.1080/00423114.2012.666353.
[22] A. Parisio, E. Rikos, and L. Glielmo. “A model predictive control approach to microgrid operation optimization”. In: IEEE Transactions on Control Systems Technology 22.5 (2014). All Open Access, Green Open Access, pp. 1813–1827. doi: 10.1109/TCST.2013.2295737.
[23] A. Parisio, E. Rikos, G. Tzamalis, and L. Glielmo. “Use of model predictive control for experimental microgrid optimization”. In: Applied Energy 115 (2014), pp. 37–46. doi: 10.1016/j.apenergy.2013.10.027.
[25] N. Fontana, M. Giugni, L. Glielmo, and G. Marini. “Real time control of a prototype for pressure regulation and energy production in water distribution networks”. In: Journal of Water Resources Planning and Management 142.7 (2016). doi: 10 .1061/(ASCE)WR.1943-5452.0000651.
[26] A. Parisio, E. Rikos, and L. Glielmo. “Stochastic model predictive control for economic/environmental operation management of microgrids: An experimental case study”. In: Journal of Process Control 43 (2016). All Open Access, Green Open Access, pp. 24–37. doi: 10.1016/j.jprocont.2016.04.008.
[27] C. Del Vecchio, F. Verrilli, L. Glielmo, and M. Corless. “A discrete time population genetic model for X-linked recessive diseases”. In: International Journal of Biology and Biomedical Engineering 11 (2017), pp. 7–15.
[29] F. Verrilli, S. Srinivasan, G. Gambino, M. Canelli, M. Himanka, C. Del Vecchio, M. Sasso, and L. Glielmo. “Model Predictive Control-Based Optimal Operations of District Heating System with Thermal Energy Storage and Flexible Loads”. In: IEEE Transactions on Automation Science and Engineering 14.2 (2017), pp. 547–557. doi: 10.1109/TASE.2016.2618948.
[30] N. Fontana, M. Giugni, L. Glielmo, G. Marini, and R. Zollo. “Hydraulic and electric regulation of a prototype for real-time control of pressure and hydropower generation in a water distribution network”. In: Journal of Water Resources Planning and Management 144.11 (2018). doi: 10.1061/(ASCE)WR.1943-5452.0001004.
[31] N. Fontana, M. Giugni, L. Glielmo, G. Marini, and R. Zollo. “Real-time control of pressure for leakage reduction in water distribution network: Field experiments”. In: Journal of Water Resources Planning and Management 144.3 (2018). doi: 10.1061/(ASCE)WR.1943-5452.0000887.
[32] N. Fontana, M. Giugni, L. Glielmo, G. Marini, and F. Verrilli. “Real-time control of a PRV in water distribution networks for pressure regulation: Theoretical framework and laboratory experiments”. In: Journal of Water Resources Planning and Management 144.1 (2018). doi: 10.1061/(ASCE)WR.1943-5452.0000855.9
[33] A. Subramanian, A. Capalbo, N. R. Iyengar, R. Rizzo, A. di Campli, R. Di Martino, M. Lo Monte, A. R. Beccari, A. Yerudkar, C. Del Vecchio, L. Glielmo, G. Turacchio, M. Pirozzi, S. G. Kim, P. Henklein, J. Cancino, S. Parashuraman, D. Diviani, F. Fanelli, M. Sallese, and A. Luini. “Auto-regulation of Secretory Flux by Sensing and Responding to the Folded Cargo Protein Load in the Endoplasmic Reticulum”. In: Cell 176.6 (2019). All Open Access, Bronze Open Access, 1461–1476.e23. doi: 10.1016/j.cell.2019.01.035.
[34] A. Acernese, A. Yerudkar, L. Glielmo, and C. Del Vecchio. “Double deep-Q learning-based output tracking of probabilistic Boolean control networks”. In: IEEE Access 8 (2020). All Open Access, Gold Open Access, Green Open Access, pp. 199254–199265. doi: 10.1109/ACCESS.2020.3035152.
[35] M. Dan, S. Srinivasan, S. Sundaram, A. Easwaran, and L. Glielmo. “A Scenario-Based Branch-and-Bound Approach for MES Scheduling in Urban Buildings”. In: IEEE Transactions on Industrial Informatics 16.12 (2020). All Open Access, Green Open Access, pp. 7510–7520. doi: 10.1109/TII.2020.2978870.
[36] A. Forootani, M. Tipaldi, M. G. Zarch, D. Liuzza, and L. Glielmo. “A Least-Squares Temporal Difference based method for solving resource allocation problems”. In: IFAC Journal of Systems and Control 13 (2020). All Open Access, Green Open Access. doi: 10.1016/j.ifacsc.2020.100106.
[37] M. A. Tajeddini, H. Kebriaei, and L. Glielmo. “Decentralized Hierarchical Planning of PEVs Based on Mean-Field Reverse Stackelberg Game”. In: IEEE Transactions on Automation Science and Engineering 17.4 (2020), pp. 2014–2024. doi: 10.1109/TASE.2020.2986374.
[38] A. Yerudkar, C. Del Vecchio, and L. Glielmo. “Feedback stabilization control design for switched Boolean control networks”. In: Automatica 116 (2020). doi: 10.1016/j.automatica.2020.108934.
[39] A. Yerudkar, C. Del Vecchio, and L. Glielmo. “Output tracking control design of switched Boolean control networks”. In: IEEE Control Systems Letters 4.2 (2020), pp. 355–360. doi: 10.1109/LCSYS.2019.2928474.
[40] M. B. Abdelghany, M. F. Shehzad, D. Liuzza, V. Mariani, and L. Glielmo. “Optimal operations for hydrogen-based energy storage systems in wind farms via model predictive control”. In: International Journal of Hydrogen Energy 46.57 (2021). All Open Access, Green Open Access, Hybrid Gold Open Access, pp. 29297–29313. doi: 10.1016/j.ijhydene.2021.01.064.
[41] A. Acernese, A. Yerudkar, L. Glielmo, and C. Del Vecchio. “Model-Free Self- Triggered Control Co-Design for Probabilistic Boolean Control Networks”. In: IEEE Control Systems Letters 5.5 (2021), pp. 1639–1644. doi: 10.1109/LCSYS.2020.3042394.
[42] A. Acernese, A. Yerudkar, L. Glielmo, and C. Del Vecchio. “Reinforcement Learning Approach to Feedback Stabilization Problem of Probabilistic Boolean Control Networks”. In: IEEE Control Systems Letters 5.1 (2021), pp. 337–342. doi: 10.1109/LCSYS.2020.3001993.10
[43] A. Forootani, D. Liuzza, M. Tipaldi, and L. Glielmo. “Allocating resources via price management systems: a dynamic programming-based approach”. In: International Journal of Control 94.8 (2021), pp. 2123–2143. doi: 10.1080/00207179.2019.1694178.
[44] A. Forootani, M. Tipaldi, M. Ghaniee Zarch, D. Liuzza, and L. Glielmo. “Modelling and solving resource allocation problems via a dynamic programming approach”. In: International Journal of Control 94.6 (2021), pp. 1544–1555. doi: 10.1080/00207179.2019.1661521.
[45] M. B. Abdelghany, M. F. Shehzad, V. Mariani, D. Liuzza, and L. Glielmo. “Two-stage model predictive control for a hydrogen-based storage system paired to a wind farm towards green hydrogen production for fuel cell electric vehicles”. In: International Journal of Hydrogen Energy 47.75 (2022). All Open Access, Hybrid Gold Open Access, pp. 32202–32222. doi: 10.1016/j.ijhydene.2022.07.136.
[47] V. Mariani, F. Zenith, and L. Glielmo. “Operating Hydrogen-Based Energy Storage Systems in Wind Farms for Smooth Power Injection: A Penalty Fees Aware Model Predictive Control”. In: Energies 15.17 (2022). All Open Access, Gold Open Access. doi: 10.3390/en15176307.
[48] M. Mazzoleni, K. Sarda, A. Acernese, L. Russo, L. Manfredi, L. Glielmo, and C. Del Vecchio. “A fuzzy logic-based approach for fault diagnosis and condition monitoring of industry 4.0 manufacturing processes”. In: Engineering Applications of Artificial Intelligence 115 (2022). doi: 10.1016/j.engappai.2022.105317.
[49] Z. Zhou, Y. Liu, J. Lu, and L. Glielmo. “Cluster Synchronization of Boolean Networks under State-Flipped Control with Reinforcement Learning”. In: IEEE Transactions on Circuits and Systems II: Express Briefs 69.12 (2022), pp. 5044–5048. doi: 10.1109/TCSII.2022.3199786.
[50] A. Joshi, M. Tipaldi, and L. Glielmo. “A Consensus Q-Learning Approach for Decentralized Control of Shared Energy Storage”. In: IEEE Control Systems Letters 7 (2023), pp. 3447–3452. doi: 10.1109/LCSYS.2023.3329072.
[51] L. Russo, S. H. Nair, L. Glielmo, and F. Borrelli. “Learning for Online Mixed-Integer Model Predictive Control With Parametric Optimality Certificates”. In: IEEE Control Systems Letters 7 (2023). All Open Access, Green Open Access, pp. 2215–2220. doi: 10.1109/LCSYS.2023.3285778.
[52] M. B. Abdelghany, V. Mariani, D. Liuzza, and L. Glielmo. “Hierarchical model predictive control for islanded and grid-connected microgrids with wind generation and hydrogen energy storage systems”. In: International Journal of Hydrogen Energy 51 (2024). All Open Access, Hybrid Gold Open Access, pp. 595–610. doi: 10.1016/j.ijhydene.2023.08.056.
[53] M. B. Abdelghany, V. Mariani, D. Liuzza, O. R. Natale, and L. Glielmo. “A Unified Control Platform and Architecture for the Integration of Wind-Hydrogen Systems into the Grid”. In: IEEE Transactions on Automation Science and Engineering 21.3 (2024). All Open Access, Hybrid Gold Open Access, pp. 4042–4057. doi: 10.1109/TASE.2023.3292029.11
[54] J. Deng, M. Tipaldi, L. Glielmo, P. R. Massenio, and L. Del Re. “A dynamic programming approach for energy management in hybrid electric vehicles under uncertain driving conditions”. In: International Journal of Systems Science 55.7 (2024), pp. 1304–1325. doi: 10.1080/00207721.2024.2304666.
[55] E. Musicò, C. Ancona, F. Lo Iudice, and L. Glielmo. “An Optimal Control Approach for Enhancing Efficiency in Renewable Energy Communities”. In: IEEE Control Systems Letters (2024). doi: 10.1109/LCSYS.2024.3521193.
Amit Joshi
Mario Terlizzi
Vishal Kachhad
Valerio Mariani was born in 1979 in Florence, Italy. He received a Ph.D. degree in automatic control from the University of Sannio, Benevento, Italy, in 2014. He was a Guest Ph.D. student with the Microgrid Research Program, Department of Energy Technology, Faculty of Engineering and Science, Aalborg University, Aalborg, Denmark.
Currently, I am working as a research scientist at GRACE (Group for Research in Automatic Control Engineering) group, Università Degli Studi del Sannio. I coordinated and managed several European/Italian projects, supervision of Ph.D. students, and scientific research. Relevant topics are optimization algorithms and energy management systems for (micro/mini) grids and path planning for autonomous vehicles. As an EE, I am passionate about electronics, and I try to devote some free time to developing embedded systems inspired by my research topics.
Amol Yerudkar received the Bachelor’s degree in Electronics Engineering and the Master’s degree in Electrical Engineering (specialization in Control Systems) from the University of Mumbai, India, in 2009 and 2012, respectively. From January 2016 to January 2020, he was a PhD student at the University of Sannio, Benevento, Italy, where he is currently a post-doc researcher with the GRACE (Group of Research on Automatic Control Engineering). His current research interests include systems biology, control of logical networks and learning for control.