MIRPALab.it - Publications

Journal Papers

[1]

A. Bicchi, A. Fagiolini, and L. Pallottino, “Toward a society of robots: Behaviors, misbehaviors, and security,” IEEE Robotics and Automation Magazine, vol. 17, no. 4, pp. 26–36, 2010, doi: 10.1109/MRA.2010.938839.

[2]

A. Fagiolini and A. Bicchi, “On the robust synthesis of logical consensus algorithms for distributed intrusion detection,” Automatica, vol. 49, no. 8, pp. 2339–2350, 2013, doi: 10.1016/j.automatica.2013.04.033.

[3]

F. Alonge, F. D’Ippolito, A. Fagiolini, and A. Sferlazza, “Extended complex kalman filter for sensorless control of an induction motor,” Control Engineering Practice, vol. 27, no. 1, pp. 1–10, 2014, doi: 10.1016/j.conengprac.2014.02.007.

[4]

F. Alonge, T. Cangemi, F. D’Ippolito, A. Fagiolini, and A. Sferlazza, “Convergence analysis of extended kalman filter for sensorless control of induction motor,” IEEE Transactions on Industrial Electronics, vol. 62, no. 4, pp. 2341–2352, 2015, doi: 10.1109/TIE.2014.2355133.

[5]

G. Oliva, D. La Manna, A. Fagiolini, and R. Setola, “Distributed data clustering via opinion dynamics,” International Journal of Distributed Sensor Networks, vol. 2015, 2015, doi: 10.1155/2015/753102.

[6]

A. Fagiolini, N. Dubbini, S. Martini, and A. Bicchi, “Convergence analysis of distributed set-valued information systems,” IEEE Transactions on Automatic Control, vol. 61, no. 6, pp. 1477–1491, 2016, doi: 10.1109/TAC.2015.2480176.

[7]

C. Bernardeschi, A. Domenici, A. Fagiolini, and M. Palmieri, “Block-based models and theorem proving in model-based development,” Electronic Communications of the EASST, vol. 79, pp. 1–8, 2020, Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111371081&partnerID=40&md5=e68299571bfecde0aecfffecfdb3b3d1

[8]

A. Fagiolini, M. Trumic, and K. Jovanovic, “An input observer-based stiffness estimation approach for flexible robot joints,” IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1843–1850, 2020, doi: 10.1109/LRA.2020.2969952.

[9]

S. Pedone and A. Fagiolini, “Racecar longitudinal control in unknown and highly-varying driving conditions,” IEEE Transactions on Vehicular Technology, vol. 69, no. 11, pp. 12521–12535, 2020, doi: 10.1109/TVT.2020.3023059.

[10]

F. Alonge, F. D’Ippolito, A. Fagiolini, G. Garraffa, and A. Sferlazza, “Trajectory robust control of autonomous quadcopters based on model decoupling and disturbance estimation,” International Journal of Advanced Robotic Systems, vol. 18, no. 2, 2021, doi: 10.1177/1729881421996974.

[11]

S. I. Azid, K. Kumar, M. Cirrincione, and A. Fagiolini, “Robust motion control of nonlinear quadrotor model with wind disturbance observer,” IEEE Access, vol. 9, pp. 149164–149175, 2021, doi: 10.1109/ACCESS.2021.3124609.

[12]

S. I. Azid, K. Kumar, M. Cirrincione, and A. Fagiolini, “Wind gust estimation for precise quasi-hovering control of quadrotor aircraft,” Control Engineering Practice, vol. 116, 2021, doi: 10.1016/j.conengprac.2021.104930.

[13]

M. Trumic, C. D. Santina, K. Jovanovic, and A. Fagiolini, “Adaptive control of soft robots based on an enhanced 3D augmented rigid robot matching,” IEEE Control Systems Letters, vol. 5, no. 6, pp. 1934–1939, 2021, doi: 10.1109/LCSYS.2020.3047737.

[14]

M. Trumić, K. Jovanović, and A. Fagiolini, “Decoupled nonlinear adaptive control of position and stiffness for pneumatic soft robots,” International Journal of Robotics Research, vol. 40, no. 1, pp. 277–295, 2021, doi: 10.1177/0278364920903787.

[15]

F. Alonge et al., “Nonlinear robust control of a quadratic boost converter in a wide operation range, based on extended linearization method,” Electronics (Switzerland), vol. 11, no. 15, 2022, doi: 10.3390/electronics11152336.

[16]

S. Pedone, M. Trumic, K. Jovanovic, and A. Fagiolini, “Robust and decoupled position and stiffness control for electrically-driven articulated soft robots,” IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 9059–9066, 2022, doi: 10.1109/LRA.2022.3188903.

[17]

V. P. Shankaran, S. I. Azid, U. Mehta, and A. Fagiolini, “Improved performance in quadrotor trajectory tracking using MIMO PI-d control,” IEEE Access, vol. 10, pp. 110646–110660, 2022, doi: 10.1109/ACCESS.2022.3214810.

[18]

M. Trumic, G. Grioli, K. Jovanovic, and A. Fagiolini, “Force/torque-sensorless joint stiffness estimation in articulated soft robots,” IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 7036–7043, 2022, doi: 10.1109/LRA.2022.3178467.

[19]

C. Bernardeschi, A. Domenici, A. Fagiolini, and M. Palmieri, “Co-simulation and formal verification of co-operative drone control with logic-based specifications,” Computer Journal, vol. 66, no. 2, pp. 295–317, 2023, doi: 10.1093/comjnl/bxab161.

[20]

S. Pedone and A. Fagiolini, “Robust discrete-time lateral control of racecars by unknown input observers,” IEEE Transactions on Control Systems Technology, vol. 31, no. 3, pp. 1418–1426, 2023, doi: 10.1109/TCST.2022.3214054.

[21]

M. Trumic, C. D. Santina, K. Jovanovic, and A. Fagiolini, “On the stability of the soft pendulum with affine curvature: Open-loop, collocated closed-loop, and switching control,” IEEE Control Systems Letters, vol. 7, pp. 385–390, 2023, doi: 10.1109/LCSYS.2022.3187612.

[22]

S. I. Azid, S. A. Ali, M. Kumar, M. Cirrincione and A. Fagiolini, "Precise Trajectory Tracking of Multi-Rotor UAVs using Wind Disturbance Rejection Approach," in IEEE Access, 2023, Early Access, doi:10.1109/ACCESS.2023.3308297.

[23]

M. Palmieri, C. Quadri, A. Fagiolini, C. Bernardeschi "Co-simulated digital twin on the network edge: A vehicle platoon," in Computer Communications, 2023, Early Access, doi:10.1016/j.comcom.2023.09.019.

[24]

C. Bernardeschi, A. Domenici, A. Fagiolini, and M. Palmieri. “Design and Validation of Cyber- Physical Systems Through Co-Simulation: The Voronoi Tessellation Use Case”, In: IEEE Access (2024), pp. 1064–1075.

[25]

C. Bernardeschi, A. M. Palmieri, C. Quadri, A. Fagiolini, and C. Bernardeschi. “Co-simulated digital twin on the network edge: A vehicle platoon”. In: Computer Communications, 2023, pp. 35– 47.

[26]

S. Pedone and A. Fagiolini. “Robust Discrete-Time Lateral Control of Racecars by Unknown Input Observers”. In: IEEE Transactions on Control Systems Technology, 2023. pp. 1418–1426.

Conference Papers

[1]

A. Fagiolini, H. Arisumi, and A. Bicchi, “Visual-based feedback control of casting manipulation,” Proceedings - IEEE International Conference on Robotics and Automation, vol. 2005. pp. 2191–2196, 2005. doi: 10.1109/ROBOT.2005.1570438.

[2]

A. Fagiolini, L. Greco, A. Bicchi, B. Piccoli, and A. Marigo, “Symbolic control for underactuated differentially flat systems,” Proceedings - IEEE International Conference on Robotics and Automation, vol. 2006. pp. 1649–1654, 2006. doi: 10.1109/ROBOT.2006.1641943.

[3]

A. Fagiolini, G. Valenti, L. Pallottino, G. Dini, and A. Bicchi, “Decentralized intrusion detection for secure cooperative multi-agent systems,” Proceedings of the IEEE Conference on Decision and Control. pp. 1553–1558, 2007. doi: 10.1109/CDC.2007.4434902.

[4]

A. Fagiolini, G. Valenti, L. Pallottino, G. Dini, and A. Bicchi, “Local monitor implementation for decentralized intrusion detection in secure multi-agent systems,” Proceedings of the 3rd IEEE International Conference on Automation Science and Engineering, IEEE CASE 2007. pp. 454–459, 2007. doi: 10.1109/COASE.2007.4341717.

[5]

L. Greco, A. Fagiolini, A. Bicchi, and B. Piccoli, “Steering dynamical systems with finite plans and limited path length,” 2007 European Control Conference, ECC 2007. pp. 4685–4690, 2007. doi: 10.23919/ecc.2007.7068855.

[6]

A. Bicchi, A. Fagiolini, G. Dini, and I. M. Savino, “Tolerating malicious monitors in detecting misbehaving robots,” Proceedings of the 2008 IEEE International Workshop on Safety, Security and Rescue Robotics, SSRR 2008. pp. 109–114, 2008. doi: 10.1109/SSRR.2008.4745886.

[7]

A. Fagiolini, M. Pellinacci, G. Valenti, G. Dini, and A. Bicchi, “Consensus-based distributed intrusion detection for multi-robot systems,” Proceedings - IEEE International Conference on Robotics and Automation. pp. 120–127, 2008. doi: 10.1109/ROBOT.2008.4543196.

[8]

A. Fagiolini, L. Tani, A. Bicchi, and G. Dini, “Decentralized deployment of mobile sensors for optimal connected sensing coverage,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5067 LNCS, pp. 486–491, 2008, doi: 10.1007/978-3-540-69170-9_34.

[9]

A. Fagiolini, E. M. Visibelli, and A. Bicchi, “Logical consensus for distributed network agreement,” Proceedings of the IEEE Conference on Decision and Control. pp. 5250–5255, 2008. doi: 10.1109/CDC.2008.4738964.

[10]

S. Alicino et al., “A rough-terrain, casting robot for the ESA lunar robotics challenge,” 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009. pp. 3336–3342, 2009. doi: 10.1109/IROS.2009.5354067.

[11]

A. Fagiolini, F. Babboni, and A. Bicchi, “Dynamic distributed intrusion detection for secure multi-robot systems,” Proceedings - IEEE International Conference on Robotics and Automation. pp. 2723–2728, 2009. doi: 10.1109/ROBOT.2009.51526.

[12]

A. Fagiolini, S. Martini, and A. Bicchi, “Set-valued consensus for distributed clock synchronization,” 2009 IEEE International Conference on Automation Science and Engineering, CASE 2009. pp. 116–121, 2009. doi: 10.1109/COASE.2009.5234145.

[13]

A. Fagiolini, S. Martini, N. Dubbini, and A. Bicchi, “Distributed consensus on boolean information,” IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 1. pp. 72–77, 2009. doi: 10.3182/20090924-3-IT-4005.0064.

[14]

A. Fagiolini, F. A. W. Belo, M. G. Catalano, F. Bonomo, S. Alicino, and A. Bicchi, “Design and control of a novel 3D casting manipulator,” Proceedings - IEEE International Conference on Robotics and Automation. pp. 4169–4174, 2010. doi: 10.1109/ROBOT.2010.5509829.

[15]

A. Fagiolini, S. Martini, D. Di Baccio, and A. Bicchi, “A self-routing protocol for distributed consensus on logical information,” IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings. pp. 5151–5156, 2010. doi: 10.1109/IROS.2010.5650096.

[16]

S. Manca, A. Fagiolini, and L. Pallottino, “Decentralized coordination system for multiple AGVs in a structured environment,” IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 44. pp. 6005–6010, 2011. doi: 10.3182/20110828-6-IT-1002.01877.

[17]

S. Martini, D. Di Baccio, A. Fagiolini, and A. Bicchi, “Robust network agreement on logical information,” IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 44. pp. 13905–13911, 2011. doi: 10.3182/20110828-6-IT-1002.03553.

[18]

S. Martini, A. Fagiolini, G. Zichittella, M. Egerstedt, and A. Bicchi, “Decentralized classification in societies of autonomous and heterogenous robots,” Proceedings - IEEE International Conference on Robotics and Automation. pp. 32–39, 2011. doi: 10.1109/ICRA.2011.5979760.

[19]

S. Martini, A. Fagiolini, L. Giarre, and A. Bicchi, “Identification of distributed systems with logical interaction structure,” Proceedings of the IEEE Conference on Decision and Control. pp. 5228–5233, 2012. doi: 10.1109/CDC.2012.6426124.

[20]

L. Cancemi, A. Fagiolini, and L. Pallottino, “Distributed multi-level motion planning for autonomous vehicles in large scale industrial environments,” IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. 2013. doi: 10.1109/ETFA.2013.6647973.

[21]

G. Conte et al., “ROAD project: Robotics for assisted diving,” 2014 22nd Mediterranean Conference on Control and Automation, MED 2014. pp. 853–856, 2014. doi: 10.1109/MED.2014.6961480.

[22]

A. Fagiolini, G. Dini, and A. Bicchi, “Distributed intrusion detection for the security of industrial cooperative robotic systems,” IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 19. pp. 7610–7615, 2014. doi: 10.3182/20140824-6-za-1003.02666.

[23]

A. Fagiolini, M. Housh, A. Ostfeld, and A. Bicchi, “Distributed estimation and control of water distribution networks by logical consensus,” ISCCSP 2014 - 2014 6th International Symposium on Communications, Control and Signal Processing, Proceedings. pp. 239–242, 2014. doi: 10.1109/ISCCSP.2014.6877859.

[24]

G. Oliva, D. L. Manna, A. Fagiolini, and R. Setola, “Distance-constrained data clustering by combined k-means algorithms and opinion dynamics filters,” 2014 22nd Mediterranean Conference on Control and Automation, MED 2014. pp. 612–619, 2014. doi: 10.1109/MED.2014.6961441.

[25]

A. D’Alessandro et al., “A low cost customizable micro-ROV for environmental research-applications, advances and challenges,” 2nd Applied Shallow Marine Geophysics Conference, Near Surface Geoscience 2016. 2016. doi: 10.3997/2214-4609.201602151.

[26]

A. D’Alessandro et al., “Characterization of MEMS accelerometer self-noise by means of PSD and allan variance analysis,” Proceedings - 2017 7th International Workshop on Advances in Sensors and Interfaces, IWASI 2017. pp. 159–164, 2017. doi: 10.1109/IWASI.2017.7974238.

[27]

G. Vitale, A. D’Alessandro, A. Costanza, and A. Fagiolini, “Low-cost underwater navigation systems by multi-pressure measurements and AHRS data,” OCEANS 2017 - Aberdeen, vol. 2017–October. pp. 1–5, 2017. doi: 10.1109/OCEANSE.2017.8084621.

[28]

D. Caporale et al., “A planning and control system for self-driving racing vehicles,” IEEE 4th International Forum on Research and Technologies for Society and Industry, RTSI 2018 - Proceedings. 2018. doi: 10.1109/RTSI.2018.8548444.

[29]

A. Domenici, A. Fagiolini, and M. Palmieri, “Integrated simulation and formal verification of a simple autonomous vehicle,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10729 LNCS, pp. 300–314, 2018, doi: 10.1007/978-3-319-74781-1_21.

[30]

A. Duz, S. Phillips, A. Fagiolini, R. G. Sanfelice, and F. Pasqualetti, “Stealthy attacks in cloud-connected linear impulsive systems,” Proceedings of the American Control Conference, vol. 2018–June. pp. 146–152, 2018. doi: 10.23919/ACC.2018.8431900.

[31]

H. K. Mudaliar, D. M. Kumar, S. I. Azid, M. Cirrincione, A. Fagiolini, and M. Pucci, “Dynamical compensation of the load torque in a high-performance electrical drive with an induction motor,” ICEMS 2018 - 2018 21st International Conference on Electrical Machines and Systems. pp. 1235–1240, 2018. doi: 10.23919/ICEMS.2018.8549162.

[32]

G. Oliva, A. Gasparri, A. Fagiolini, and C. N. Hadjicostis, “Distributed and proximity-constrained c-means for discrete coverage control,” 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, vol. 2018–January. pp. 1584–1589, 2018. doi: 10.1109/CDC.2017.8263877.

[33]

M. Palmieri, C. Bernardeschi, A. Domenici, and A. Fagiolini, “Demo: Co-simulation of UAVs with INTO-CPS and PVSio-web,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11176 LNCS, pp. 52–57, 2018, doi: 10.1007/978-3-030-04771-9_5.

[34]

C. Sciortino and A. Fagiolini, “ROS/gazebo-based simulation of quadcopter aircrafts,” IEEE 4th International Forum on Research and Technologies for Society and Industry, RTSI 2018 - Proceedings. 2018. doi: 10.1109/RTSI.2018.8548411.

[35]

F. Alonge, F. D’Ippolito, A. Fagiolini, G. Garraffa, F. M. Raimondi, and A. Sferlazza, “Tuning of extended kalman filters for sensorless motion control with induction motor,” 2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019. 2019. doi: 10.23919/EETA.2019.8804540.

[36]

C. Bernardeschi, A. Fagiolini, M. Palmieri, G. Scrima, and F. Sofia, “ROS/gazebo based simulation of co-operative UAVs,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11472 LNCS, pp. 321–334, 2019, doi: 10.1007/978-3-030-14984-0_24.

[37]

D. Caporale et al., “Towards the design of robotic drivers for full-scale self-driving racing cars,” Proceedings - IEEE International Conference on Robotics and Automation, vol. 2019–May. pp. 5643–5649, 2019. doi: 10.1109/ICRA.2019.8793882.

[38]

C. Bernardeschi, A. Domenici, M. Palmieri, and A. Fagiolini, “Co-simulation of bio-inspired multi-agent algorithms,” Simulation Series, vol. 52. pp. 230–241, 2020. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099293028&partnerID=40&md5=66ed886db913d175169f25decb944481

[39]

K. Kumar, S. I. Azid, A. Fagiolini, and M. Cirrincione, “Erle-copter simulation using ROS and gazebo,” 20th IEEE Mediterranean Electrotechnical Conference, MELECON 2020 - Proceedings. pp. 259–263, 2020. doi: 10.1109/MELECON48756.2020.9140476.

[40]

M. Trumić, K. Jovanović, and A. Fagiolini, “Comparison of model-based simultaneous position and stiffness control techniques for pneumatic soft robots,” Mechanisms and Machine Science, vol. 84, pp. 218–226, 2020, doi: 10.1007/978-3-030-48989-2_24.

[41]

D. M. Kumar, M. Cirrincione, H. K. Mudaliar, M. Di Benedetto, A. Lidozzi, and A. Fagiolini, “Development of a fractional PI controller in an FPGA environment for a robust high-performance PMSM electrical drive,” Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021. pp. 2427–2431, 2021. doi: 10.1109/ECCE-Asia49820.2021.9479450.

[42]

H. K. Mudaliar, D. M. Kumar, M. Cirrincione, M. Di Benedetto, and A. Fagiolini, “Improving the speed estimation by load torque estimation in induction motor drives: An MRAS and NUIO approach,” Proceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021. pp. 2421–2426, 2021. doi: 10.1109/ECCE-Asia49820.2021.9479249.

[43]

M. Trumic, C. Della Santina, K. Jovanovic, and A. Fagiolini, “Adaptive control of soft robots based on an enhanced 3D augmented rigid robot matching,” Proceedings of the American Control Conference, vol. 2021–May. pp. 4991–4996, 2021. doi: 10.23919/ACC50511.2021.9482817.

[44]

S. S. Chand et al., “Enhanced current loop PI controllers with adaptive feed-forward neural network via estimation of grid impedance: Application to three-phase grid-tied PV inverters,” 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022. 2022. doi: 10.1109/ECCE50734.2022.9947752.

[45]

J. Mazal et al., “Preface,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13207 LNCS, p. v, 2022, Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128765366&partnerID=40&md5=81784e64b10e219ff66b63b805aa43fc

[46]

A. Mohammadi, A. Fagiolini, M. Cirrincione, E. Garone, A. Garone, and D. Varagnolo, “Towards an open database of assessment material for STEM subjects: Requirements and recommendations from early field trials,” IFAC-PapersOnLine, vol. 55. pp. 7–12, 2022. doi: 10.1016/j.ifacol.2022.09.217.

[47]

H. K. Mudaliar, A. Fagiolini, M. Cirrincione, S. S. Chand, R. Prasad, and D. Kumar, “Adaptive feed-forward neural network for wind power delivery,” 2022 International Conference on Electrical Machines and Systems, ICEMS 2022. 2022. doi: 10.1109/ICEMS56177.2022.9983098.

[48]

M. Palmieri, C. Quadri, A. Fagiolini, G. P. Rossi, and C. Bernardeschi, “Co-simulated digital twin on the network edge: The case of platooning,” Proceedings - 2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2022. pp. 613–618, 2022. doi: 10.1109/WoWMoM54355.2022.00096.

[49]

S. Pedone and A. Fagiolini, “Robust longitudinal control of self-driving racecar models,” 2022 European Control Conference, ECC 2022. pp. 796–801, 2022. doi: 10.23919/ECC55457.2022.9837984.

[50]

R. Prasad et al., “Enhancing speed loop PI controllers with adaptive feed-forward neural networks: Application to induction motor drives,” 2022 International Conference on Electrical Machines and Systems, ICEMS 2022. 2022. doi: 10.1109/ICEMS56177.2022.9983335.