Lei Xi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Lei Xi has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Haochen Zhang
College of Electrical and Information Engineering, Lanzhou University of Technology, China
1 shared publication - Jianrong Liu
Gansu Natural Energy Institute, Lanzhou 730000, China
1 shared publication - Wenxu Zhang
School of Automation and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730050, China
1 shared publication - Yangming Fan
Institute of Automation, Gansu Academy of Sciences, Lanzhou 730030, China
1 shared publication
Latest Publications
- Open Access
A Novel P + d Control Scheme for Time-Delayed Telerobotic Systems with Damping Adjustment
This paper presents a novel Proportional Damping Injection (P + d) control scheme that incorporates a damping regulation strategy and an adaptive method for networked telerobotic systems. Unlike the traditional P + d controller with a fixed damping coefficient, the proposed approach includes a dynamic damping adjuster, designed based on position error, to enhance the position tracking speed and improve the system robustness. To address uncertainties in dynamic models and external forces, Radial Basis Function (RBF) neural networks and an adaptive strategy are employed for dynamic estimation. The closed-loop stability of the teleoperation system was rigorously established using the Lyapunov–Krasovskii method, and the relationship between the controller gains and communication delay boundaries was explicitly derived. Finally, simulations and experimental results validated the system’s stability and effectiveness, demonstrating the advantages of the proposed controller.
Open AccessA Novel P + d Control Scheme for Time-Delayed Telerobotic Systems with Damping Adjustment
This paper presents a novel Proportional Damping Injection (P + d) control scheme that incorporates a damping regulation strategy and an adaptive method for networked telerobotic systems. Unlike the traditional P + d controller with a fixed damping coefficient, the proposed approach includes a dynamic damping adjuster, designed based on position error, to enhance the position tracking speed and improve the system robustness. To address uncertainties in dynamic models and external forces, Radial Basis Function (RBF) neural networks and an adaptive strategy are employed for dynamic estimation. The closed-loop stability of the teleoperation system was rigorously established using the Lyapunov–Krasovskii method, and the relationship between the controller gains and communication delay boundaries was explicitly derived. Finally, simulations and experimental results validated the system’s stability and effectiveness, demonstrating the advantages of the proposed controller.