Papers
9
Total Citations
324
H-Index
6
About
Xinkai Chen is a prominent control systems researcher whose work spans adaptive control theory, intelligent robotics, and smart material actuation. His research is distinguished by the development of sophisticated control frameworks—including adaptive pseudoinverse methods, fuzzy neural networks, and impedance control strategies—designed to handle the nonlinearities, constraints, and uncertainties inherent in complex robotic systems. Chen's most influential contribution, "Adaptive Pseudoinverse Control for Constrained Hysteretic Nonlinear Systems" (2023, 119 citations), advances the control of dielectric elastomer actuators, enabling more precise and reliable performance in soft biomimetic and rehabilitation robots. His parallel body of work on constrained robotic manipulators, combining barrier Lyapunov functions with disturbance observers and neural network approximators, has garnered over 120 additional citations, cementing his authority in robust adaptive control for manipulation tasks. Particularly noteworthy is Chen's sustained focus on rehabilitation robotics, including assist-as-needed controllers that balance patient safety with active therapeutic engagement. More recently, his group has extended these methods to quadrotor UAVs and surgical robot trajectory planning, reflecting impressive breadth. With a growing citation record and contributions spanning over two decades—from sampled-data systems to fixed-time stochastic control—Chen represents a significant and evolving voice in intelligent control engineering.
Research Focus
Key Achievements
Top Papers
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- 6Control of uncertain sampled-data systems7 citations · 2001
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