Papers
2
Total Citations
18
H-Index
2
About
Zhuoran Zhang is an emerging researcher working at the intersection of advanced electrical machines and intelligent control systems. His work spans two compelling domains: high-performance permanent magnet synchronous machines (PMSMs) for aeronautical applications and adaptive neural network-based control for robotic systems. In his 2024 survey on PMSMs, Zhang contributed a comprehensive analysis of recent developments and trends in machine design for aerospace environments — a field where demands for high power density, efficiency, and dynamic response are particularly stringent — garnering 12 citations in its first year alone. Complementing this hardware-focused research, his work on adaptive iterative learning control (AILC) for long-stroke hybrid robots tackles the challenging problem of trajectory tracking under initial errors and full state constraints, employing radial basis function (RBF) neural networks to handle system uncertainties, earning 6 citations since publication. Together, these contributions reflect Zhang's dual expertise in electromechanical systems and intelligent control theory. His early-career output suggests a researcher poised to make meaningful contributions to the design and precise control of next-generation aerospace and robotic platforms.
Research Focus
Key Achievements
Top Papers
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