Paolo Stegagno’s Research Profile

Stegagno, Paolo, 2021

Recent Grants1

Grant Portion Amount
4/3/2020. Co-PI. National Science Foundation. “Collaborative Research: Towards Computationally Efficient One-Shot Design for Performance Guaranteed Distributed Multi-Agent Control.” $206,594.00 (50%) of total $413,188.00

Recent Publications1

Citation Journal Impact Factor
Zhang J, Yuan C, Stegagno S, Zeng W. Fault Isolation of a Class of Uncertain Nonlinear Parabolic PDE Systems. Modeling, Estimation and Control Conference, 2022
Zhang J, Chen X, Stegagno P, Yuan C. Nonlinear Dynamics Modeling and Fault Detection for A Soft Trunk Robot: An Adaptive NN-based approach. IEEE Robotics and Automation Letters, 2022. doi: 10.1109/LRA.2022.3184034 2021 JIF 5.427
Zhang J, Gu Y, Stegagno S, Zeng W, Yuan C. Adaptive NN-Based Reference-Tracking Control of Uncertain Nonlinear Parabolic PDE Systems. 2021 60th IEEE Confrence on Decision and Control(CDC), 2021; 4052-4057. doi: 10.1109/CDC45484.2021.9683381
Masone C, Stegagno P. Shared Control of an Aerial Cooperative Transportation System with a Cable-suspended Payload. Journal of intelligent & Robotic Systems, 2021; 103(3), 1-29. doi: 10.1007/s10846-021-01457-4 2021 JIF 3.611
Brent S, Yuan C, Stegagno P. Cooperative place recognition in robotic swarms. Proceedings of the 36th Annual ACM Symposium on Applied Computing, 2021; 785-792. doi: 10.1145/3412841.3441954
Yuan C., Stegagno P., He HB., Ren W. Cooperative Adaptive Containment Control with Parameter Convergence via Cooperative Finite-Time Excitation. IEEE Transactions on Automatic Control, 2020; 1-1. doi: 10.1109/TAC.2021.3056336 2021 JIF 6.116, 2020 JIF 6.594
Zhang J., Yuan C., Zang W., Stegagno P., Wang C. Fault Detection of a Class of Nonlinear Uncertain Parabolic PDE Systems. IEEE Control Systems Letters, 2020; 5(4), 1459-1464. doi: 10.1109/LCSYS.2020.3040132 2021 JIF 2.766, 2020 JIF 2.950
Chen X, Stegagno P, Yuan Deterministic Learning with Probabilistic Analysis on Human-Robot Shared Contro. 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2020; 1304-1309. doi: 10.1109/AIM43001.2020.9158798
Dong X, Chen X, Yuan C, Stegagno New Results on Cooperative Multi-Vehicle Deterministic Learning Control: Design and Validation in Gazebo Simulation. 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2020; 1413-1418. doi: 10.1109/AIM43001.2020.9158929
Yuan C, Gu Y, Zeng W, Stegagno Switching Model Predictive Control of Switched Linear Systems with Average Dwell Time. 2020 American Control Conference (ACC), 2020; 2888-2893. doi: 10.23919/ACC45564.2020.9147362
Zhang J, Yuan C, Stegagno P. Similar fault isolation of discrete-time nonlinear uncertain systems using smallest residual principle. 2020 American Control Conference (ACC), 2020; 3176-3181. doi: 10.23919/ACC45564.2020.9147429
Zhang J, Yuan C, Wang C, Stegagno P, Zeng W. Composite Adaptive NN Learning and Control for Discrete-Time Nonlinear Uncertain Systems in Normal Form. Neurocomputing, 2020; 390, 168-184. doi: 10.1016/j.neucom.2020.01.052 2021 JIF 6.192, 2020 JIF 6.610
Zhang J, Yuan C, Stegagno P, Zeng W, Wang C. Small Fault Detection from Discrete-Time Closed-Loop Control Using Fault Dynamics Residuals. Neurocomputing, 2019; 365, 239-248. doi: 10.1016/j.neucom.2019.07.037 2021 JIF 6.192,  2019 JIF 5.913
Zhang J, Yuan C, Stegagno P, He H, Wang C. Small Fault Detection of Discrete-Time Nonlinear Uncertain Systems. IEEE Transactions on Cybernetics, 2019; 1-15. doi: 10.1109/TCYB.2019.2945629 2021 JIF 11.784, 2019 JIF 11.220
Zhang J, Yuan C, Stegagno Adaptive NN Learning Control of Discrete-Time Nonlinear Uncertain Systems. Dynamic Systems and Control Conference, 2019; 59162, V003T16A002. doi: 10.1115/DSCC2019-8923
Zhang J, Yuan C, Stegagno P. Adaptive Dynamics Learning for Small Fault Detection of Discrete-Time Nonlinear Uncertain Systems. ASME 2019 Dynamic Systems and Control Conference, 2019; 59148, V001T06A002. doi:1115/DSCC2019-8913
Chen X, Stegagno P, Dong X, Yuan C. Kinect-Based Human Gait Recognition Using a Novel Adaptive Dynamics Learning Approach. ASME 2019 Dynamic Systems and Control Conference, 2019; doi: 10.1115/DSCC2019-8920
Yuan C, Zeng W, Stegagno P. Cooperative Exact State Estimation of Linear Multi-Agent Systems with Heterogeneous Bounded Disturbances. 2019 Chinese Control Conference (CCC), 2019; 5811-5816. doi: 10.23919/ChiCC.2019.8866573
Chen X, Dong X, Zeng W, Yuan C, Stegagno P. UGV Direction Control by Human Arm Gesture Recognition via Deterministic Learning. 2019 Chinese Control Conference (CCC), 2019; 7688-7693. doi: 10.23919/ChiCC.2019.8865788
Dong X, Yuan C, Stegagno P, Zeng W, Wang C. Composite Cooperative Synchronization and Decentralized Learning of Multi-Robot Manipulators with Heterogeneous Nonlinear Uncertain Dynamics. Journal of the Franklin Institute, 2019; 356(10), 5049-5072. doi: 10.1016/j.jfranklin.2019.04.028 2021 JIF 4.483, 2019 JIF 4.743
Maggi B, Baxter C, Grilli A, et al. Field Performance of Reinforced Dunes for Improving Coastal Resilience. Geo-Congress 2019: Soil Erosion, Underground Engineering, and Risk Assessment, 2019; 53-56. doi: 10.1061/9780784482155.006
Stegagno P, Yuan C. Distributed Cooperative Adaptive State Estimation and System Identification for Multi-Agent Systems. IET Control Theory and Applications, 2019; 13(6), 815-822. doi: 10.1049/iet-cta.2018.6113 2021 JIF 2.884, 2019 JIF 4.153
Maggi B, Baxter C, Bradshaw A, et al. Development of Fragility Curves for Reinforced Dunes. Coastal Engineering Proceedings, 2018; 1(36), 10. doi: 10.9753/icce.v36.structures.10
Yaun C, Abdelatti M, Dong X, Zeng W, Stegnano P, Duan C. Cooperative Deterministic Learning Control of Multi-Robot Manipulators. 2018 37th Chinese Control Conference (CCC), 2018; 2824-2829. doi: 10.23919/ChiCC.2018.8483021
Odelga M, Stegagno P, Kochanek N, Bulthoff H, et al. A Self-Contained Teleoperated Quadrotor: On-Board State Estimation and Indoor Obstacle IEEE International Conference on Robotics and Automation (ICRA 2018), 2018; 7840-7847. doi: 10.1109/ICRA.2018.8463185

 

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