What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Robot
Zhijun Li mainly focuses on Control theory, Robot, Adaptive control, Trajectory and Artificial neural network.
Zhijun Li has included themes like Control engineering and Exoskeleton in his Control theory study.
His work in Robot addresses subjects such as Simulation, which are connected to disciplines such as Exponential stability.
His studies in Adaptive control integrate themes in fields like Markov process, Robust control and Motion control.
He works mostly in the field of Artificial neural network, limiting it down to concerns involving Robustness and, occasionally, Observer and Impedance control.
His Control theory research integrates issues from Stability, Motion, Computer vision and Vehicle dynamics.
His most cited work include:
- Neural network-based motion control of an underactuated wheeled inverted pendulum model. (222 citations)
- Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision (220 citations)
- Teleoperation Control Based on Combination of Wave Variable and Neural Networks (207 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Control theory, Robot, Artificial intelligence, Trajectory and Control engineering.
His Artificial neural network research extends to Control theory, which is thematically connected.
His Robot study combines topics in areas such as Simulation and Exoskeleton.
His research investigates the connection between Artificial intelligence and topics such as Computer vision that intersect with problems in Obstacle avoidance.
His Trajectory research is multidisciplinary, incorporating perspectives in Mathematical optimization, Task analysis and Inverted pendulum.
His Control engineering study combines topics from a wide range of disciplines, such as Mobile manipulator, Motion and Motion control.
He most often published in these fields:
- Control theory (56.27%)
- Robot (44.95%)
- Artificial intelligence (26.61%)
What were the highlights of his more recent work (between 2019-2021)?
- Robot (44.95%)
- Control theory (56.27%)
- Artificial intelligence (26.61%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Robot, Control theory, Artificial intelligence, Trajectory and Control theory.
His Human–robot interaction, Teleoperation and Robot manipulator study in the realm of Robot connects with subjects such as Scheme.
His Control theory research incorporates elements of Artificial neural network and Exoskeleton.
His Artificial intelligence research is multidisciplinary, incorporating elements of Construct, Machine learning and Computer vision.
His research integrates issues of Task, Task analysis, Function, Workspace and Optimization problem in his study of Trajectory.
Zhijun Li interconnects Admittance and Robot kinematics, Mobile robot in the investigation of issues within Control theory.
Between 2019 and 2021, his most popular works were:
- High-Order Disturbance-Observer-Based Sliding Mode Control for Mobile Wheeled Inverted Pendulum Systems (47 citations)
- Admittance-Based Controller Design for Physical Human–Robot Interaction in the Constrained Task Space (29 citations)
- Reinforcement Learning Control of a Flexible Two-Link Manipulator: An Experimental Investigation (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Computer vision
His main research concerns Control theory, Robot, Trajectory, Control theory and Exoskeleton.
Control theory and Bounded function are commonly linked in his work.
The various areas that he examines in his Robot study include Motion and Task.
His biological study spans a wide range of topics, including Admittance, Lyapunov function, Mobile robot, Manipulator and Reinforcement learning.
His studies deal with areas such as Observer, Robot kinematics and Actuator as well as Control theory.
His Exoskeleton research includes elements of Control engineering, Workspace, Cog and Inverted pendulum.
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