activity
20152025
most citedNeuro-Adaptive Formation Control and Target Tracking for Nonlinear Multi-Agent Systems with Time-Delay

64 citations · 94 across the 7 of their papers we have counts for

collaborators

7 papers

eess.SY2025

Stability and Convergence Analysis of Multi-Agent Consensus with Communication Delays: A Lambert W Function Approach

Layan Badran, Kiarash Aryankia, Rastko R. Selmic

This paper investigates the effect of constant time delay in weakly connected multi-agent systems modeled by double integrator dynamics. A novel analytical approach is proposed to…

eess.SY2022

Cyberattack Detection for Nonlinear Leader-Following Multi-Agent Systems Using Set-Membership Fuzzy Filtering

Mahshid Rahimifard, Amir M. Moradi Sizkouhi, Rastko R. Selmic

This paper is concerned with cyberattack detection in discrete-time, leader-following, nonlinear, multi-agent systems subject to unknown but bounded (UBB) system noises. The Takagi…

eess.SY2022★ 13 cited

Formation Control of Nonlinear Multi-Agent Systems Using Three-Layer Neural Networks

Kiarash Aryankia, Rastko R. Selmic

This paper considers a leader-following formation control problem for heterogeneous, second-order, uncertain, input-affine, nonlinear multi-agent systems modeled by a directed grap…

eess.SY2021

Cyber-Attack Detection in Discrete Nonlinear Multi-Agent Systems Using Neural Networks

Amirreza Mousavi, Kiarash Aryankia, Rastko R. Selmic

This paper proposes a distributed cyber-attack detection method in communication channels for a class of discrete, nonlinear, heterogeneous, multi-agent systems that are controlled…

eess.SY2020★ 64 cited

Neuro-Adaptive Formation Control and Target Tracking for Nonlinear Multi-Agent Systems with Time-Delay

Kiarash Aryankia, Rastko R. Selmic

This paper proposes an adaptive neural network-based backstepping controller that uses rigid graph theory to address the distance-based formation control problem and target trackin…

cs.LG2017★ 2 cited

Classifying Unordered Feature Sets with Convolutional Deep Averaging Networks

Andrew Gardner, Jinko Kanno, Christian A. Duncan +1

Unordered feature sets are a nonstandard data structure that traditional neural networks are incapable of addressing in a principled manner. Providing a concatenation of features i…