182 citations · 225 across the 20 of their papers we have counts for
21 papers
DR-IPC: Disturbance-Resilient Integrated Planning and Control for LiDAR-Based Quadrotor Navigation
Peng Liu, Jingyan Wang, Qipeng Ye +5
LiDAR-based quadrotor navigation in cluttered environments remains challenging under external disturbances, particularly when obstacle-aware motion generation and disturbance-rejec…
Self-Gating Attention for Efficient Time Series Forecasting
Dezheng Wang, Tong Chen, Wei Yuan +3
Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal dependencies across historical…
Autonomous UAV Pipeline Near-proximity Inspection via Disturbance-Aware Predictive Visual Servoing
Wen Li, Hui Wang, Jinya Su +3
Reliable pipeline inspection is critical to safe energy transportation, but is constrained by long distances, complex terrain, and risks to human inspectors. Unmanned aerial vehicl…
MPC as a Copilot: A Predictive Filter Framework with Safety and Stability Guarantees
Yunda Yan, Chenxi Tao, Jinya Su +2
Ensuring both safety and stability remains a fundamental challenge in learning-based control, where goal-oriented policies often neglect system constraints and closed-loop state co…
LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly Detection
Dezheng Wang, Tong Chen, Guansong Pang +3
As a fundamental data mining task, unsupervised time series anomaly detection (TSAD) aims to build a model for identifying abnormal timestamps without assuming the availability of…
Auto-Optimization with Active Learning in Uncertain Environment: A Predictive Control Approach
Yuan Tan, Jun Yang, Zhongguo Li +2
This paper presents an auto-optimal model predictive control (MPC) framework enhanced with active learning, designed to autonomously track optimal operational conditions in an unkn…
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…
An Approach to Mismatched Disturbance Rejection Control for Continuous-Time Uncontrollable Systems
Shichao Lv, Hongdan Li, Kai Peng +2
This paper focuses on optimal mismatched disturbance rejection control for linear continuoustime uncontrollable systems. Different from previous studies, by introducing a new quadr…
A distributionally robust optimization approach to two-sided chance constrained stochastic model predictive control with unknown noise distribution
Yuan Tan, Jun Yang, Wen-Hua Chen +1
In this work, we propose a distributionally robust stochastic model predictive control (DR-SMPC) algorithm to address the problem of two-sided chance constrained discrete-time line…
Multi-step dual control for exploration and exploitation in autonomous search with convergence guarantee
Yuan Tan, Jun Yang, Wen-Hua Chen +1
Motivated by the recently proposed dual control for exploration and exploitation (DCEE) concept, this paper presents a Multi-Step DCEE (MS-DCEE) framework with guaranteed convergen…
Active Disturbance Rejection Control Design with Suppression of Sensor Noise Effects in Application to DC-DC Buck Power Converter
Krzysztof Łakomy, Rafal Madonski, Bin Dai +4
The performance of active disturbance rejection control (ADRC) algorithms can be limited in practice by high-frequency measurement noise. In this work, this problem is addressed by…
Robust converter-fed motor control based on active rejection of multiple disturbances
Rafal Madonski, Krzysztof Łakomy, Momir Stankovic +3
In this work, an advanced motion controller is proposed for buck converter-fed DC motor systems. The design is based on an idea of active disturbance rejection control (ADRC) with…
An Adaptive Passivity-Based Controller of a Buck-Boost Converter With a Constant Power Load
Wei He, Romeo Ortega, Juan E. Machado +1
This paper addresses the problem of regulating the output voltage of a DC-DC buck-boost converter feeding a constant power load,which is a problem of current practical interest. De…