activity
20212026
most citedData-Driven Resilient Predictive Control under Denial-of-Service

5 citations · 5 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CV2026

Depth-Semantic Alignment and Affinity-Guided Fusion for Structured Radar Point Cloud Generation

Amjad Hussain, Wenjie Liu, Yuchen Tan +4

Point clouds are an important carrier of three-dimensional spatial information, and their quality directly affects the performance of downstream perception tasks such as object det…

eess.SY2026

Data-driven Kernel-based Predictive Control with Stability and Robustness Guarantees

Wenjie Liu, Yifei Li, Gang Wang +1

In this paper, we provide a theoretical analysis of the closed-loop properties of a data-driven kernel-based predictive control (DDKPC) scheme developed solely from input-output da…

eess.SY2026

Data-Driven Robust MPC for Unknown Nonlinear Systems via Set-Membership Learning

Yuzhou Wei, Wenjie Liu, Yifan Xie +3

Data-driven model predictive control (MPC) has become an attractive approach for controlling unknown systems, especially when data are corrupted by noise. However, most existing da…

eess.SY2026

Robust Data-Driven Nash Equilibrium Seeking under Partial-Decision Information

Linqi Wang, Yifei Li, Wenjie Liu +3

This paper presents a data-driven framework for decentralized Nash equilibrium (NE) seeking in multi-agent systems with unknown linear dynamics subject to exogenous disturbances, o…

eess.SY2026

Data-Driven Frequency-Selective Output Regulation of Nonlinear Systems under Almost Periodic Exosignals

Yifei Li, Wenjie Liu, Gang Wang +1

This paper studies output regulation for a class of unknown continuous-time nonlinear systems driven by almost periodic exosignals. The plant dynamics are assumed to be linearly pa…

eess.SY2025

Learning event-triggered controllers for linear parameter-varying systems from data

Renjie Ma, Su Zhang, Wenjie Liu +2

Nonlinear dynamical behaviours in engineering applications can be approximated by linear-parameter varying (LPV) representations, but obtaining precise model knowledge to develop a…