Papers
13
Total Citations
325
H-Index
8
About
Zhouhua Peng is a prominent researcher specializing in autonomous marine and mobile robotics, with a particular focus on cooperative control, path following, disturbance rejection, and intelligent motion control of unmanned surface vehicles (USVs). His work sits at the intersection of nonlinear control theory, multi-agent systems, and data-driven learning, making significant contributions to both theoretical foundations and practical implementation. Peng's most influential work, "Anti-disturbance Coordinated Path-following Control of Robotic Autonomous Surface Vehicles" (2019, 86 citations), established robust guidance and control frameworks for networked underactuated ASVs operating under real-world environmental disturbances. His subsequent research on containment maneuvering of mobile robots (2020, 61 citations) further advanced cooperative multi-agent control architectures. Notably, his 2022 paper on model-based deep reinforcement learning for USV motion control reflects his forward-looking integration of machine learning with classical control design. Across his body of work, Peng consistently bridges theory and experiment, validating results through hardware-in-the-loop simulations and physical trials. His more recent contributions on safety-certified cooperative control and data-driven extended state observers demonstrate a growing emphasis on constraint satisfaction and learning-based robustness, positioning him as a leading voice in intelligent autonomous maritime systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Path-Guided Containment Maneuvering of Mobile Robots: Theory and Experiments61 citations · 2020
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10