A5103129337- Robot Manipulation and Learning
- Teleoperation and Haptic Systems
- Reinforcement Learning in Robotics
- Robotic Mechanisms and Dynamics
- Advanced Control Systems Optimization
- Muscle activation and electromyography studies
- Railway Systems and Energy Efficiency
- Electrical Contact Performance and Analysis
- Industrial Technology and Control Systems
- Soft Robotics and Applications
- Control Systems and Identification
- Network Traffic and Congestion Control
- Dynamics and Control of Mechanical Systems
- Piezoelectric Actuators and Control
- Robotics and Automated Systems
- Advanced Neural Network Applications
- Fault Detection and Control Systems
- Iterative Learning Control Systems
Yanshan University
2011-2023
Princeton Public Schools
2019
Beijing Jiaotong University
2013-2014
Robot force control is an important issue for intelligent mobile robotics. The end-point stiffness of a robot key and open problem in the research community. strategies are mostly dependent on both specifications task environment robot. Due to limited end-effector, we may adopt inherent torque feedback oscillations controlled force. This paper proposes effective strategy which contains controller using quantitative theory. nested loop controllers take into account physical limitation...
In Communication-Based Train Control (CBTC) systems, random transmission delays and packet drops are inevitable in the wireless networks, which could result unnecessary traction, brakes or even emergency of trains, losses line capacity passenger dissatisfaction. This paper applies predictive function control technology with a mixed H 2 /∞ approach to improve performances. The controller is state feedback form satisfies requirement quadratic input constraints. A linear matrix inequality (LMI)...
Train operation is a complex nonlinear process; it difficult to establish accurate mathematical model. In this paper, we design ATO speed controller based on the input and output data of train operation. The method combines multimodeling with predictive functional control according complicated characteristics Firstly, cluster sample by using fuzzy-c means algorithm. Secondly, identify parameter model recursive least square algorithm forgetting factor then local set models process Then at...
This paper works on hybrid force/position control in robotic manipulation and proposes an improved radial basis functional (RBF) neural network, which is a robust relying the Hamilton Jacobi Issacs principle of force loop. The method compensates uncertainties robot system by using property RBF network. error approximation network regarded as external interference system, it eliminated method. Since conventionally fixed structure not optimal, resource allocating (RAN) proposed this to adjust...
Trajectory generation is a fundamental problem for successful robotic grasping. However, most of the existing work dealt with this using supervised learning prescribed model. It prevents developed grasp strategies from being used new unknown scenarios. In paper, inspired by success reinforcement method, we method which optimizes trajectories policy search method. An important advantage proposed that complicated 3D model could be to generate multi-dimensional configurations. The algorithm has...