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Research PaperResearchia:202606.26050

Resilient Output Containment under Undisclosed Leader Dynamics and Actuator Attacks

Mohammadreza Nematollahi

Abstract

This work studies resilient output containment for heterogeneous linear multi-agent systems with actuator cyber-attacks over directed network topologies. The leaders generate bounded locally absolutely continuous trajectories; however, their dynamics, velocity bounds, and motion envelopes are undisclosed to the followers. The cyber-attack model includes state- and input-correlated, as well as bounded exogenous actuator false-data terms. A continuous two-layer adaptive control architecture is pro...

Submitted: June 26, 2026Subjects: AI; AI Agents

Description / Details

This work studies resilient output containment for heterogeneous linear multi-agent systems with actuator cyber-attacks over directed network topologies. The leaders generate bounded locally absolutely continuous trajectories; however, their dynamics, velocity bounds, and motion envelopes are undisclosed to the followers. The cyber-attack model includes state- and input-correlated, as well as bounded exogenous actuator false-data terms. A continuous two-layer adaptive control architecture is proposed. The first layer is a virtual-actuator reconfiguration layer that uses partial state measurements to compensate for actuator attacks in the local tracking-error dynamics. The second layer is a network interface that generates task-space commands via an adaptive interaction protocol. This protocol uses only neighbor-exchanged network-interface states whose dimensions match those of the plant output, and it does not require global graph knowledge for parameter tuning. For directed graphs, under a leader-rooted united spanning-tree condition, a nonsmooth Lyapunov analysis yields asymptotic containment at the command level. The physical outputs then converge to the leader convex hull up to a residual determined by the command-tracking local controllers. Simulation results using a network of quadrotors with damped suspended loads illustrate the performance of attack recovery and containment tracking.


Source: arXiv:2606.27257v1 - http://arxiv.org/abs/2606.27257v1 PDF: https://arxiv.org/pdf/2606.27257v1 Original Link: http://arxiv.org/abs/2606.27257v1

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Submission Info
Date:
Jun 26, 2026
Topic:
AI Agents
Area:
AI
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Resilient Output Containment under Undisclosed Leader Dynamics and Actuator Attacks | Researchia