Ye Pu
Orcid: 0000-0001-5924-0859
According to our database1,
Ye Pu
authored at least 43 papers
between 2013 and 2024.
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Bibliography
2024
A Geometry-Based Distributed Connectivity Maintenance Algorithm for Discrete-time Multi-Agent Systems with Visual Sensing Constraints.
Unmanned Syst., March, 2024
Non-Asymptotic Bounds for Closed-Loop Identification of Unstable Nonlinear Stochastic Systems.
CoRR, 2024
Towards Fast and Safety-Guaranteed Trajectory Planning and Tracking for Time-Varying Systems.
CoRR, 2024
A Control Barrier Function Composition Approach for Multi-Agent Systems in Marine Applications.
CoRR, 2024
Proceedings of the Computer Vision - ECCV 2024, 2024
2023
Sub-Optimal Moving Horizon Estimation in Feedback Control of Linear Constrained Systems.
IEEE Control. Syst. Lett., 2023
Learning-Based Adaptive Control for Stochastic Linear Systems With Input Constraints.
IEEE Control. Syst. Lett., 2023
Proceedings of the IEEE International Conference on Robotics and Automation, 2023
Proceedings of the Conference on Robot Learning, 2023
Stability Bounds for Learning-Based Adaptive Control of Discrete-Time Multi-Dimensional Stochastic Linear Systems with Input Constraints.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
2022
Real-Time Distributed Model Predictive Control with Limited Communication Data Rates.
CoRR, 2022
Safety-guaranteed trajectory planning and control based on GP estimation for unmanned surface vessels.
CoRR, 2022
Proceedings of the IEEE Conference on Control Technology and Applications, 2022
Trajectory planning for multiple autonomous underwater vehicles with safety guarantees.
Proceedings of the Australian & New Zealand Control Conference, 2022
2021
A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications.
IEEE Trans. Autom. Control., 2021
FaSTrack: A Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking.
IEEE Trans. Autom. Control., 2021
Real-time Distributed MPC for Multiple Underwater Vehicles with Limited Communication Data-rates.
Proceedings of the 2021 American Control Conference, 2021
Path Following by Formations of Agents with Collision Avoidance Guarantees using Distributed Model Predictive Control.
Proceedings of the 2021 American Control Conference, 2021
2020
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2020
Proceedings of the 16th IEEE International Conference on Control & Automation, 2020
Safety-Guaranteed Real-Time Trajectory Planning for Underwater Vehicles in Plane-Progressive Waves.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020
2019
SVR-AMA: An Asynchronous Alternating Minimization Algorithm With Variance Reduction for Model Predictive Control Applications.
IEEE Trans. Autom. Control., 2019
2018
CoRR, 2018
Plug and Play Distributed Model Predictive Control for Heavy Duty Vehicle Platooning and Interaction with Passenger Vehicles.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
Proceedings of the 2018 Annual American Control Conference, 2018
2017
Complexity Certification of the Fast Alternating Minimization Algorithm for Linear MPC.
IEEE Trans. Autom. Control., 2017
Proceedings of the 55th Annual Allerton Conference on Communication, 2017
2016
Proceedings of the 55th IEEE Conference on Decision and Control, 2016
Proceedings of the 2nd IEEE International Conference on Big Data Security on Cloud, 2016
Proceedings of the 2016 American Control Conference, 2016
2015
Proceedings of the 54th IEEE Conference on Decision and Control, 2015
Proceedings of the American Control Conference, 2015
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015
2014
Proceedings of the 13th European Control Conference, 2014
Inexact fast alternating minimization algorithm for distributed model predictive control.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014
2013
IEEE Trans. Signal Process., 2013
Plug and play distributed model predictive control based on distributed invariance and optimization.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013