Zikai Hu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Zikai Hu has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Fang Wang
College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China
1 shared publication - Jianhui Wang
Guangzhou University
1 shared publication - Jiarui Liu
Guangzhou University
1 shared publication - Ruizhi Tang
School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
1 shared publication - Weicong Huang
School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
1 shared publication - Yixiang Gu
School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China
1 shared publication
Latest Publications
- Open Access
Adaptive Self-Triggered Control for Multi-Agent Systems with Actuator Failures and Time-Varying State Constraints
This work focuses on the consensus problem for multi-agent systems (MASs) with actuator failures and time-varying state constraints, and presents a fixed-time self-triggered consensus control protocol. The use of time-varying asymmetrical barrier Lyapunov functions (BLF) avoids the violation of time-varying state constraints in MASs, ensuring stability and safety. Meanwhile, the system’s performance is further enhanced by leveraging the proposed adaptive neural networks (NNs) control method to mitigate the effects of actuator failures and nonlinear disturbances. Moreover, a self-triggered mechanism based on a fixed-time strategy is proposed to reach rapid convergence and conserve bandwidth resources in MASs. The mechanism achieves consensus within a predefined fixed time, irrespective of the system’s initial states, while conserving communication resources. Finally, the proposed method’s effectiveness is confirmed through two simulation examples, encompassing diverse actuator failure scenarios.
Open AccessAdaptive Self-Triggered Control for Multi-Agent Systems with Actuator Failures and Time-Varying State Constraints
This work focuses on the consensus problem for multi-agent systems (MASs) with actuator failures and time-varying state constraints, and presents a fixed-time self-triggered consensus control protocol. The use of time-varying asymmetrical barrier Lyapunov functions (BLF) avoids the violation of time-varying state constraints in MASs, ensuring stability and safety. Meanwhile, the system’s performance is further enhanced by leveraging the proposed adaptive neural networks (NNs) control method to mitigate the effects of actuator failures and nonlinear disturbances. Moreover, a self-triggered mechanism based on a fixed-time strategy is proposed to reach rapid convergence and conserve bandwidth resources in MASs. The mechanism achieves consensus within a predefined fixed time, irrespective of the system’s initial states, while conserving communication resources. Finally, the proposed method’s effectiveness is confirmed through two simulation examples, encompassing diverse actuator failure scenarios.