Papers
12
Total Citations
375
H-Index
7
About
Dan Jiang is a leading researcher in advanced nonlinear control for electro-hydraulic actuation and robotic systems, with a particular focus on exoskeleton technology. His major contributions lie in developing robust adaptive and saturated control strategies that address critical challenges such as parametric uncertainty, load disturbance, and control saturation in electro-hydraulic servo systems. His seminal work, "Saturated Adaptive Control of an Electrohydraulic Actuator with Parametric Uncertainty and Load Disturbance" (95 citations), along with his highly cited "Robust H∞ positional control of 2-DOF robotic arm" (87 citations), have set benchmarks in the field. Jiang's research has directly advanced human-robot interaction, notably through his work on a 2-DOF lower limb exoskeleton platform (46 citations), where he applied backpropagation neural networks for torque detection. He has also pioneered model identification techniques using biogeography-based learning particle swarm optimization and neighborhood field optimization algorithms. With over 370 total citations across his top publications, Jiang's work continues to influence the design of more precise, stable, and wearable robotic systems for rehabilitation and industrial applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10