E. Nozari and F. Pasqualetti and J. Cortés, Heterogeneity of central nodes explains the benefits of time-varying control scheduling in complex dynamical networks. Journal of Complex Networks, 1-43, 2019. [PDF]
S. Zhao and F. Pasqualetti, Networks with Diagonal Controllability Gramians: Analysis, Graphical Conditions, and Design Algorithms. Automatica, 102:10-18, 2019. [PDF]
G. Bianchin and F. Pasqualetti, Gramian-Based Optimization for the Analysis and Control of Traffic Networks. IEEE Transactions on Intelligent Transportation Systems, 1-12, 2019.
E. J. Cornblath and E. Tang and G. L. Baum and T. M. Moore and A. Abedimpe and D. R. Roalf and R. C. Gur and R. E. Gur and F. Pasqualetti and T. D. Satterthwaite and D. S. Bassett, Sex differences in network controllability as a predictor of executive function in youth. Neuroimage, 122-134, 2019. [PDF]
J. Stiso and A. N. Khambhati and T. Menara and A. E. Kahn and J. M. Stein and S. R. Das and R. Gorniak and J. Tracy and B. Litt and K. A. Davis and F. Pasqualetti and T. H. Lucas and D. S. Bassett, White Matter Network Architecture Guides Direct Electrical Stimulation through Optimal State Transitions. Cell Reports, 28(10):2554 - 2566.e7, 2019. [PDF]
F. Pasqualetti and S. Gu and D. S. Bassett, RE: Warnings and caveats in brain controllability. NeuroImage, 197:586-588, 2019.
G. Baggio and V. Katewa and F. Pasqualetti, Data-driven Minimum-Energy Controls for Linear Systems. IEEE Control Systems Letters, 3(3):589-594, 2019. [PDF]
A. A. Al Makdah and V. Katewa and F. Pasqualetti, A Fundamental Performance Limitation for Adversarial Classification. IEEE Control Systems Letters, 4(1):169-174, 2019. [PDF]
G. Bianchin and Y.-C. Liu and F. Pasqualetti, Secure Navigation of Robots in Adversarial Environments. IEEE Control Systems Letters, 4(1):1-6, 2019. [PDF]
T. Menara and D. S. Bassett and F. Pasqualetti, Structural Controllability of Symmetric Networks. IEEE Transactions on Automatic Control, 64(9):3740-3747, 2019. [PDF]
T. Menara and G. Baggio and D. S. Bassett and F. Pasqualetti, A Framework to Control Functional Connectivity in the Human Brain. IEEE Conf. on Decision and Control, Nice, France, pages 4697-4704, December 2019. [PDF]
G. Baggio and V. Katewa and F. Pasqualetti and S. Zampieri, The Shannon Capacity of Linear Dynamical Networks. European Control Conference, Naples, Italy, June 2019.
G. Bianchin and F. Pasqualetti and S. Kundu, Resilience of Traffic Networks with Partially Controlled Routing. American Control Conference, Philadelphia, PA, USA, July 2019.
R. Anguluri and V. Katewa and F. Pasqualetti, A Probabilistic Approach to Design Switching Attacks against Interconnected Systems. American Control Conference, Philadelphia, PA, USA, July 2019.
T. Menara and G. Baggio and D. S. Bassett and F. Pasqualetti, Exact and Approximate Stability Conditions for Cluster Synchronization of Kuramoto Oscillators. American Control Conference, Philadelphia, PA, USA, pages 205 - 210, July 2019. [PDF]
D. S. Bassett and F. Pasqualetti, Network-based approaches for understanding intrinsic control capacities of the human brain. The Cognitive Neurosciences VI. Ed. by M. S. Gazzaniga and G. R. Mangun and D. Poeppel. MIT Press, 2019. In press.
V. Katewa and F. Pasqualetti and V. Gupta, On the Role of Cooperation in Private Multi-agent Systems. Privacy in Dynamical Systems. Ed. by F. Farokhi. Springer Nature, 2019.
F. Pasqualetti, Controllability of network systems. Encyclopedia of Systems and Control. Ed. by J. Baillieul and T. Samad. Springer Nature, 2019. In press.
Fabio Pasqualetti - University of California at