182 citations · 225 across the 20 of their papers we have counts for
9 papers · 1 filter
Learning and Current Prediction of PMSM Drive via Differential Neural Networks
Wenjie Mei, Xiaorui Wang, Yanrong Lu +2
Learning models for dynamical systems in continuous time is significant for understanding complex phenomena and making accurate predictions. This study presents a novel approach ut…
ICODE: Modeling Dynamical Systems with Extrinsic Input Information
Zhaoyi Li, Wenjie Mei, Ke Yu +2
Learning models of dynamical systems with external inputs, which may be, for example, nonsmooth or piecewise, is crucial for studying complex phenomena and predicting future state…
Admittance Visuomotor Policy Learning for General-Purpose Contact-Rich Manipulations
Bo Zhou, Ruixuan Jiao, Yi Li +3
Contact force in contact-rich environments is an essential modality for robots to perform general-purpose manipulation tasks, as it provides information to compensate for the defic…
Arbitrary-Order Distributed Finite-Time Differentiator for Multi-Agent Systems
Weile Chen, Haibo Du, Shihua Li +1
This paper proposes arbitrary-order distributed finite-time differentiator (AODFD) for leader-follower multi-agent systems (MAS) under directed graph by only using relative or abso…
Flexible Active Safety Motion Control for Robotic Obstacle Avoidance: A CBF-Guided MPC Approach
Jinhao Liu, Jun Yang, Jianliang Mao +5
A flexible active safety motion (FASM) control approach is proposed for the avoidance of dynamic obstacles and the reference tracking in robot manipulators. The distinctive feature…
Guarding Force: Safety-Critical Compliant Control for Robot-Environment Interaction
Xinming Wang, Jun Yang, Jianliang Mao +3
In this study, we propose a safety-critical compliant control strategy designed to strictly enforce interaction force constraints during the physical interaction of robots with unk…
Active Admittance Control with Iterative Learning for General-Purpose Contact-Rich Manipulation
Bo Zhou, Yuyao Sun, Wenbo Liu +3
Force interaction is inevitable when robots face multiple operation scenarios. How to make the robot competent in force control for generalized operations such as multi-tasks still…
Distributed Finite-time Differentiator for Multi-agent Systems Under Directed Graph
Weile Chen, Haibo Du, Shihua Li
This paper proposes a new distributed finite-time differentiator (DFD) for multi-agent systems (MAS) under directed graph, which extends the differentiator algorithm from the centr…
Composite learning control with modular backstepping and high-order tuners
Tian Shi, Shihua Li, Changyun Wen +1
Adaptive control of strict-feedback nonlinear systems with mismatched uncertainties remains challenging because high-order derivatives of parameter estimates can degrade transient…