Wei Zhao
Orcid: 0009-0009-6560-0000Affiliations:
- Huazhong University of Science and Technology, Department of Aerospace Engineering, School of Mechanical Science and Engineering, Wuhan, China
According to our database1,
Wei Zhao
authored at least 14 papers
between 2015 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
Reinforcement Learning-Based Predefined-Time Tracking Control for Nonlinear Systems Under Identifier-Critic-Actor Structure.
IEEE Trans. Cybern., November, 2024
Dynamic Leader-Follower Output Containment Control of Heterogeneous Multiagent Systems Using Reinforcement Learning.
IEEE Trans. Syst. Man Cybern. Syst., September, 2024
Predefined-Time Event-Triggered Tracking Control for Nonlinear Servo Systems: A Fuzzy Weight-Based Reinforcement Learning Scheme.
IEEE Trans. Fuzzy Syst., August, 2024
Distributed Model-Free Optimal Control for Multiagent Pursuit-Evasion Differential Games.
IEEE Trans. Netw. Sci. Eng., 2024
2023
Adaptive fuzzy fixed-time tracking control for high-order nonlinear delayed systems with mismatched disturbances.
J. Frankl. Inst., November, 2023
J. Frankl. Inst., February, 2023
2021
Nearly Optimal Integral Sliding-Mode Consensus Control for Multiagent Systems With Disturbances.
IEEE Trans. Syst. Man Cybern. Syst., 2021
2019
Data-Driven Distributed Optimal Consensus Control for Unknown Multiagent Systems With Input-Delay.
IEEE Trans. Cybern., 2019
IEEE Access, 2019
2018
IEEE Trans. Cybern., 2018
Finite-time distributed formation tracking control of multi-UAVs with a time-varying reference trajectory.
IMA J. Math. Control. Inf., 2018
Stochastic leader-following consensus of multi-agent systems with measurement noises and communication time-delays.
Neurocomputing, 2018
2017
Leader-follower optimal coordination tracking control for multi-agent systems with unknown internal states.
Neurocomputing, 2017
2015
Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization.
Int. J. Distributed Sens. Networks, 2015