Zedong Hu

About

Zedong Hu is a researcher advancing the field of smart materials and robotic actuation, with a primary focus on shape memory alloy (SMA) applications. His work centers on developing innovative control strategies for flexible robotic systems, particularly in biomedical and micro-robotic contexts. Hu’s most notable contribution is his 2022 paper on the "Tracking Control of Shape Memory Alloy Artificial Wrist Joint Using Sliding Mode Control Strategy Based on RBF Neural Network," which addresses the critical challenge of precise motion control in SMA-driven actuators. By integrating radial basis function neural networks with sliding mode control, he proposed a robust method to compensate for SMA’s nonlinear hysteresis and temperature-dependent behavior, enabling more accurate and reliable joint movements. This work has garnered 3 citations, reflecting its emerging relevance in the field. Hu’s research bridges materials science and control engineering, offering practical solutions for next-generation flexible robots and aerospace mechanisms. His achievements highlight a commitment to overcoming the inherent complexities of smart materials, positioning him as a promising contributor to intelligent actuation systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Tracking Control of Shape Memory Alloy Artificial Wrist Joint Using Sliding Mode Control Strategy Based on RBF Neural Network

   3 citations · 2022

Key Collaborators

Contact & Links