Papers
2
Total Citations
10
H-Index
2
About
Dong Ming Guo is a researcher specializing in advanced control systems for robotic and pneumatic artificial muscle (PAM) applications. His work focuses on addressing critical challenges in nonlinear, uncertain, and time-varying systems, particularly for biomimetic robots and medical auxiliary devices. His most cited paper, "Angle Tracking Robust Learning Control for Pneumatic Artificial Muscle Systems" (2021, 8 citations), proposes a robust learning control strategy to overcome high nonlinearities and uncertainties in PAM systems, enabling precise angle tracking. This contribution is vital for developing more reliable and accurate biomimetic and medical devices. In his more recent work, "Singularity-Free Fixed-Time Neuro-Adaptive Control for Robot Manipulators" (2023, 2 citations), Guo introduces a novel control strategy that guarantees fixed-time convergence without singularities, even under input saturation and external disturbances—a significant advancement for trajectory tracking in complex robotic systems. By integrating neuro-adaptive techniques with auxiliary systems, his research pushes the boundaries of robust, real-time control for next-generation robots and assistive technologies.
Research Focus
Key Achievements
Top Papers
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- 2