Papers
7
Total Citations
72
H-Index
4
About
Zehua Jia is a rising researcher in robotics and control systems, specializing in autonomous underwater vehicles (AUVs), unmanned surface vessels (USVs), and redundant robot manipulators. Jia’s work centers on developing advanced motion planning and disturbance compensation techniques, with a particular focus on zeroing neural networks (ZNN) for solving time-dependent constrained problems. Their most cited paper, "Distributed dynamic rendezvous control of the AUV-USV joint system with practical disturbance compensations using model predictive control" (2022, 34 citations), introduces a novel MPC-based framework for coordinated marine robotics. Jia has made significant contributions to ZNN theory, including the "Harmonic Noise Rejection Zeroing Neural Network" (2024, 20 citations), which addresses equality-constrained quadratic programs with applications to robot arms, and discrete-time ZNNs for constrained nonlinear equations and dual-arm robot systems. Their work on acceleration-level repetitive motion planning (2023) and synchronous motion planning for dual-arm robots (2023) further demonstrates their impact in robotics. With over 70 total citations and publications spanning 2022-2025, Jia’s research bridges theoretical neural network advances with practical robotic applications, establishing them as an emerging authority in intelligent control systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7