998 citations · 2.2k across the 70 of their papers we have counts for
12 papers · 1 filter
On the Robustness of Data-Driven Controllers for Linear Systems
Rajasekhar Anguluri, Abed AlRahman Al Makdah, Vaibhav Katewa +1
This paper proposes a new framework and several results to quantify the performance of data-driven state-feedback controllers for linear systems against targeted perturbations of t…
Accuracy Prevents Robustness in Perception-based Control
Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
In this paper we prove the existence of a fundamental trade-off between accuracy and robustness in perception-based control, where control decisions rely solely on data-driven, and…
A practical guide to methodological considerations in the controllability of structural brain networks
Teresa M. Karrer, Jason Z. Kim, Jennifer Stiso +4
Predicting how the brain can be driven to specific states by means of internal or external control requires a fundamental understanding of the relationship between neural connectiv…
Learning in brain-computer interface control evidenced by joint decomposition of brain and behavior
Jennifer Stiso, Marie-Constance Corsi, Jean M. Vettel +5
Motor imagery-based brain-computer interfaces (BCIs) use an individuals ability to volitionally modulate localized brain activity as a therapy for motor dysfunction or to probe cau…
Brain state stability during working memory is explained by network control theory, modulated by dopamine D1/D2 receptor function, and diminished in schizophrenia
Urs Braun, Anais Harneit, Giulio Pergola +15
Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory entails brainwi…
Resilience of Traffic Networks with Partially Controlled Routing
Gianluca Bianchin, Fabio Pasqualetti, Soumya Kundu
This paper investigates the use of Infrastructure-To-Vehicle (I2V) communication to generate routing suggestions for drivers in transportation systems, with the goal of optimizing…
A Framework to Control Functional Connectivity in the Human Brain
Tommaso Menara, Giacomo Baggio, Danielle S. Bassett +1
In this paper, we propose a framework to control brain-wide functional connectivity by selectively acting on the brain's structure and parameters. Functional connectivity, which me…
Centralized Versus Decentralized Detection of Attacks in Stochastic Interconnected Systems
Rajasekhar Anguluri, Vaibhav Katewa, Fabio Pasqualetti
We consider a security problem for interconnected systems governed by linear, discrete, time-invariant, stochastic dynamics, where the objective is to detect exogenous attacks by p…
A Fundamental Performance Limitation for Adversarial Classification
Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
Despite the widespread use of machine learning algorithms to solve problems of technological, economic, and social relevance, provable guarantees on the performance of these data-d…
Secure Trajectory Planning Against Undetectable Spoofing Attacks
Yin-Chen Liu, Gianluca Bianchin, Fabio Pasqualetti
This paper studies, for the first time, the trajectory planning problem in adversarial environments, where the objective is to design the trajectory of a robot to reach a desired f…
Data-Driven Minimum-Energy Controls for Linear Systems
Giacomo Baggio, Vaibhav Katewa, Fabio Pasqualetti
In this paper we study the problem of computing minimum-energy controls for linear systems from experimental data. The design of open-loop minimum-energy control inputs to steer a…
The control of brain network dynamics across diverse scales of space and time
Evelyn Tang, Harang Ju, Graham L. Baum +4
The human brain is composed of distinct regions that are each associated with particular functions and distinct propensities for the control of neural dynamics. However, the relati…