Pallacci T.; Mimmo N.; Sessa P.; Rabbeni R., A Deep-Learning Model of Virtual Test Drivers, «IEEE CONTROL SYSTEMS LETTERS», 2024, 8, pp. 1150 - 1155 [Scientific article]Open Access
Mimmo, Nicola, Analysis and Design of Control Laws for Advanced Driver-Assistance Systems, Switzerland, Springer Cham, 2024, pp. 276 . [Research monograph]
Mimmo, Nicola; Carnevale, Guido; Testa, Andrea; Notarstefano, Giuseppe, Extremum Seeking Tracking for Derivative-Free Distributed Optimization, «IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS», 2024, 12, pp. 584 - 595 [Scientific article]
Carnevale, Guido; Mimmo, Nicola; Notarstefano, Giuseppe, Extremum-Seeking Policy Iteration for Data-Driven LQR, in: Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., 2024, pp. 6263 - 6267 (atti di: 63rd IEEE Conference on Decision and Control, CDC 2024, Allianz MiCo Milano Convention Centre, ita, 2024) [Contribution to conference proceedings]
Carnevale, Guido; Mimmo, Nicola; Notarstefano, Giuseppe, Nonconvex distributed feedback optimization for aggregative cooperative robotics, «AUTOMATICA», 2024, 167, pp. 111767 - 111775 [Scientific article]
Castaldi, P; Mimmo, N, Representing the dynamics of student learning and interactions with a university curriculum, in: IFAC-PapersOnLine, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, ELSEVIER, 2024, 58, pp. 211 - 216 (atti di: 2nd IFAC Workshop on Aerospace Control Education, WACE 2024, Bertinoro, Italy, July 22-24, 2024) [Contribution to conference proceedings]
Mimmo, N.; Marconi, L.; Notarstefano, G., Uniform non-convex optimisation via Extremum Seeking, «IEEE TRANSACTIONS ON AUTOMATIC CONTROL», 2024, 69, pp. 1 - 13 [Scientific article]
Carnevale G.; Mimmo N.; Notarstefano G., Aggregative feedback optimization for distributed cooperative robotics, in: IFAC-PapersOnLine, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, Elsevier B.V., 2022, 55, pp. 7 - 12 (atti di: 9th IFAC Conference on Networked Systems, NECSYS 2022, Zurich, Switzerland, 2022) [Contribution to conference proceedings]
Mimmo, Nicola; Marconi, Lorenzo; Notarstefano, Giuseppe, Uniform quasi-convex optimisation via Extremum Seeking, in: 2022 IEEE 61st Conference on Decision and Control (CDC), IEEE, 2022, pp. 6306 - 6311 (atti di: 61st IEEE Conference on Decision and Control, Cancun (Mexico), 06-09 December 2022) [Contribution to conference proceedings]Open Access
Cacace J.; Mimmo N.; Marconi L., An ARVA Sensor Simulator, in: Studies in Computational Intelligence, Cham, Springer Science and Business Media Deutschland GmbH, 2021, pp. 233 - 266 (STUDIES IN COMPUTATIONAL INTELLIGENCE) [Chapter or essay]
Castaldi P.; Mimmo N., Investigation of the student-professor interaction and self-learning ability for an aerospace engineering student, in: IFAC-PapersOnLine, Elsevier B.V., 2021, 54, pp. 1 - 6 (atti di: IFAC Workshop on Aerospace Control Education WACE 2021, Milan, Italy, 9 -10 September 2021) [Contribution to conference proceedings]
Bernard P.; Mimmo N.; Marconi L., On the Semi-Global Stability of an EK-Like Filter, «IEEE CONTROL SYSTEMS LETTERS», 2021, 5, Article number: 9290120 , pp. 1771 - 1776 [Scientific article]Open Access
Tabasso C.; Mimmo N.; Cichella V.; Marconi L., Optimal Motion Planning for Localization of Avalanche Victims by Multiple UAVs, «IEEE CONTROL SYSTEMS LETTERS», 2021, 5, Article number: 9312965 , pp. 2054 - 2059 [Scientific article]Open Access
Castaldi P.; Mimmo N., A Mathematical Model in Automatic Control Aerospace Engineering Education, in: IFAC PAPERSONLINE, Elsevier B.V., 2020, 53, pp. 17138 - 17143 (atti di: 21st IFAC World Congress 2020, Berlin (on-line), 12 - 17 July 2020) [Contribution to conference proceedings]
Cacace, Jonathan; Mimmo, Nicola; Marconi, Lorenzo, A ROS Gazebo plugin to simulate ARVA sensors, in: 2020 IEEE International Conference on Robotics and Automation (ICRA), IEEE, 2020, pp. 7233 - 7239 (atti di: 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 31 May - 31 Aug. 2020) [Contribution to conference proceedings]Open Access
