12 papers
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…
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…
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…
Composite learning control with modular backstepping and high-order tuners
Tian Shi, Shihua Li, Changyun Wen +1
This paper proposes a composite learning backstepping control (CLBC) strategy based on modular backstepping and high-order tuners to achieve closed-loop exponential stability witho…
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…
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…