Papers
17
Total Citations
211
H-Index
8
About
Zhinan Peng is a robotics and control systems researcher whose work sits at the intersection of intelligent control theory, rehabilitation engineering, and human-robot interaction. His research focuses primarily on lower limb exoskeleton robots, adaptive dynamic programming (ADP), and event-triggered control strategies, with a growing emphasis on brain-computer and neuromuscular interfaces for assistive technologies. Peng's most significant contributions lie in developing advanced learning-based control frameworks for rehabilitation exoskeletons. His 2023 paper on event-triggered critic learning impedance control has garnered 94 citations, establishing him as a leading voice in intelligent exoskeleton control. This work, alongside his event-triggered ADP methods for robotic manipulators and tracking control under uncertainty, demonstrates his ability to bridge rigorous optimal control theory with real-world rehabilitation applications. Beyond control algorithms, Peng has made notable strides in multimodal human-exoskeleton interfaces, combining EEG and surface electromyography (sEMG) signals to enable more intuitive, reliable human-robot communication. His MCSNet architecture and Assist-As-Needed gait training frameworks further reflect his commitment to patient-centered, adaptive rehabilitation systems. With over 180 cumulative citations across recent publications, Peng's work is shaping next-generation assistive robotics and neurally-driven rehabilitation technology.
Research Focus
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Top Papers
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