Papers
4
Total Citations
43
H-Index
3
About
Jing Chi is a robotics researcher whose work focuses on the intersection of adaptive control, nonlinear dynamics, and intelligent systems for mobile and agricultural robots. Chi’s major contributions lie in developing advanced control strategies that ensure robust, high-performance operation under uncertainty and disturbance. For instance, Chi has pioneered adaptive neural network-based finite-time trajectory tracking for wheeled robots (15 citations), and designed adaptive perturbation rejection control with integrated driving circuits for wheeled mobile platforms (13 citations). In a notable application to agricultural robotics, Chi applied reinforcement learning to control heavy material handling manipulators (12 citations), addressing real-world challenges in automation. Chi’s work also extends to fixed-time control, as demonstrated by a study on cart-pendulum robots that combines linear quadratic optimization with adaptive sliding mode control to guarantee path-following within a fixed time. With a growing citation record, Jing Chi is recognized for bridging theoretical control advances with practical robotic systems, making significant strides in the reliability and intelligence of autonomous platforms.
Research Focus
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Top Papers
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