T. Guo and A. A. Al Makdah and V. Krishnan and F. Pasqualetti, Imitation and Transfer Learning for LQG Control. IEEE Control Systems Letters, 7:2149-2154, 2023.
A. A. Al Makdah and V. Krishnan and F. Pasqualetti, Learning Lipschitz Feedback Policies from Expert Demonstrations: Closed-Loop Guarantees, Generalization and Robustness. IEEE Open Journal of Control Systems, 1:85-99, 2022.
D. Gadginmath and V. Krishnan and F. Pasqualetti, Data-Driven Feedback Linearization using the Koopman Generator. IEEE Transactions on Automatic Control, 2022. Submitted.
V. Krishnan and F. Pasqualetti, Data-Driven Attack Detection for Linear Systems. IEEE Control Systems Letters, 5(2):671-676, 2020. [PDF]
Conference Articles
D. Gadginmath and V. Krishnan and F. Pasqualetti, Direct vs Indirect Methods for Behavior-based Attack Detection. IEEE Conf. on Decision and Control, Cancún, Mexico, December 2022.
A. A. Al Makdah and V. Krishnan and V. Katewa and F. Pasqualetti, Behavioral Feedback for Optimal LQG Control. IEEE Conf. on Decision and Control, Cancún, Mexico, pages 4660-4666, December 2022. [PDF]
V. Krishnan and F. Pasqualetti, On Direct vs Indirect Data-Driven Predictive Control. IEEE Conf. on Decision and Control, Austin, TX, pages 736-741, December 2021.
V. Krishnan and A. A. Al Makdah and F. Pasqualetti, Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing. Advances in Neural Information Processing Systems, Vancouver, Canada, pages 10924-10935, December 2020. [PDF]