collaborators

7 papers

math.OC2026

Primal-dual algorithm for distributed optimization: A dissipativity-based perspective

Weijian Li, Panos J. Antsaklis, Hai Lin

We study a continuous-time primal-dual algorithm for distributed optimization with nonconvex local cost functions over weight-unbalanced digraphs, and analyze its performance from…

eess.SP2025

MA-enhanced Mixed Near-field and Far-field Covert Communications

Chao Zhou, Changsheng You, Cong Zhou +2

In this paper, we propose to employ a modular-based movable extremely large-scale array (XL-array) at Alice for enhancing covert communication performance. Compared with existing w…

eess.SY2025

Funnel-Based Online Recovery Control for Nonlinear Systems With Unknown Dynamics

Zihao Song, Shirantha Welikala, Panos J. Antsaklis +1

In this paper, we focus on recovery control of nonlinear systems from attacks or failures. The main challenges of this problem lie in (1) learning the unknown dynamics caused by at…

eess.SY2025

Hierarchical Analysis and Control of Epidemic Spreading over Networks using Dissipativity and Mesh Stability

Shirantha Welikala, Hai Lin, Panos J. Antsaklis

Analyzing and controlling spreading processes are challenging problems due to the involved non-linear node (subsystem) dynamics, unknown disturbances, complex interconnections, and…

eess.SY2025

Graph Neural Network-Based Distributed Optimal Control for Linear Networked Systems: An Online Distributed Training Approach

Zihao Song, Shirantha Welikala, Panos J. Antsaklis +1

In this paper, we consider the distributed optimal control problem for discrete-time linear networked systems. In particular, we are interested in learning distributed optimal cont…

eess.SY2025

Mesh Stability Guaranteed Rigid Body Networks Using Control and Topology Co-Design

Zihao Song, Shirantha Welikala, Panos J. Antsaklis +1

Merging and splitting are of great significance for rigid body networks in making such networks reconfigurable. The main challenges lie in simultaneously ensuring the compositional…