Aquib Mustafa

2 accepted papers

2025

Region-Driven Adaptation for Constrained Reinforcement Learning-Based Control

RA-L 2025

This paper presents a region-driven adaptation for constrained reinforcement learning (RL)-based control for systems with unknown nonlinear dynamics. For safety-critical control, several noteworthy results have been presented that ensure safety through the control barrier function (CBF) theory. One

Cited by 0 Source ↗Scholar ↗

2020

Attack Analysis and Resilient Control Design for Discrete-Time Distributed Multi-Agent Systems

Aquib Mustafa, Hamidreza Modares

RA-L 2020

This work analyzes the adverse effects of cyberphysical attacks on discrete-time distributed multi-agent systems, and proposes a mitigation approach for attacks on sensors and actuators. First, we show how an attack on a single node snowballs into a network-wide attack and even destabilizes the enti

Cited by 74 Source ↗Scholar ↗