5 papers
Direct vs Indirect Methods for Behavior-based Attack Detection
Darshan Gadginmath, Vishaal Krishnan, Fabio Pasqualetti
We study the problem of data-driven attack detection for unknown LTI systems using only input-output behavioral data. In contrast with model-based detectors that use errors from an…
On Direct vs Indirect Data-Driven Predictive Control
Vishaal Krishnan, Fabio Pasqualetti
In this work, we compare the direct and indirect approaches to data-driven predictive control of stochastic linear time-invariant systems. The distinction between the two approache…
Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing
Vishaal Krishnan, Abed AlRahman Al Makdah, Fabio Pasqualetti
In this work we propose a graph-based learning framework to train models with provable robustness to adversarial perturbations. In contrast to regularization-based approaches, we f…
Data-Driven Attack Detection for Linear Systems
Vishaal Krishnan, Fabio Pasqualetti
This paper studies the attack detection problem in a data-driven and model-free setting, for deterministic systems with linear and time-invariant dynamics. Differently from existin…
A Probabilistic Framework for Moving-Horizon Estimation: Stability and Privacy Guarantees
Vishaal Krishnan, Sonia Martínez
This work proposes a unifying probabilistic framework for the design of robustly asymptotically stable moving-horizon estimators (MHE) for discrete-time nonlinear systems, and a me…