Zhigang Luo
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Zhigang Luo has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Bing Zhu
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
3 shared publications - Jianying Zheng
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
1 shared publication - Xiangyu Meng
Division of Electrical and Computer engineering, Louisiana State University, Baton Rouge, LA, USA
1 shared publication - Zewei Zheng
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
1 shared publication - Zongyu Zuo
Beihang University
1 shared publication
Latest Publications
- 13 August 2024
- Published by Elsevier in Journal of the Franklin Institute
- Vol. 361 (16)
Event-based model predictive control with two-phase predictive detection
- 13 August 2024
- Published by Elsevier in Journal of the Franklin Institute
- Vol. 361 (16)
Event-based model predictive control with two-phase predictive detection
- 31 May 2024
- Published by Springer Nature in Nonlinear Dynamics
- Vol. 112 (16) , 1-15
Intermittent sampling and detection event-based model predictive control for perturbed nonlinear systems
- 31 May 2024
- Published by Springer Nature in Nonlinear Dynamics
- Vol. 112 (16) , 1-15
Intermittent sampling and detection event-based model predictive control for perturbed nonlinear systems
- 29 January 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE/CAA Journal of Automatica Sinica
- Vol. 11 (2) , 560-562
Robust Distributed Model Predictive Control for Formation Tracking of Nonholonomic Vehicles
This letter proposes a robust distributed model predictive control (MPC) strategy for formation tracking of a group of wheeled vehicles subject to constraints and disturbances. Formation control has attracted significant interest because of its applications in searching and exploration [1], [2]. The objective of formation tracking is to achieve the reference formation via interactions among agents. In formation tracking, MPC can be applied to treat constrains. In [3], by sharing predictive information with neighbors, each agent uses distributed MPC strategy to generate the desired trajectory without any collision. Based on the leader-follower structure, a distributed MPC is proposed in [4] to mitigate effects caused by replay attacks. In [5], distributed MPC is applied to optimize energy scheduling.
- 29 January 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE/CAA Journal of Automatica Sinica
- Vol. 11 (2) , 560-562
Robust Distributed Model Predictive Control for Formation Tracking of Nonholonomic Vehicles
This letter proposes a robust distributed model predictive control (MPC) strategy for formation tracking of a group of wheeled vehicles subject to constraints and disturbances. Formation control has attracted significant interest because of its applications in searching and exploration [1], [2]. The objective of formation tracking is to achieve the reference formation via interactions among agents. In formation tracking, MPC can be applied to treat constrains. In [3], by sharing predictive information with neighbors, each agent uses distributed MPC strategy to generate the desired trajectory without any collision. Based on the leader-follower structure, a distributed MPC is proposed in [4] to mitigate effects caused by replay attacks. In [5], distributed MPC is applied to optimize energy scheduling.