12 citations · 28 across the 10 of their papers we have counts for
14 papers
Imitation and Transfer Learning for LQG Control
Taosha Guo, Abed AlRahman Al Makdah, Vishaal Krishnan +1
In this paper we study an imitation and transfer learning setting for Linear Quadratic Gaussian (LQG) control, where (i) the system dynamics, noise statistics and cost function are…
Data-Driven Feedback Linearization using the Koopman Generator
Darshan Gadginmath, Vishaal Krishnan, Fabio Pasqualetti
This paper contributes a theoretical framework for data-driven feedback linearization of nonlinear control-affine systems. We unify the traditional geometric perspective on feedbac…
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…
Behavioral Feedback for Optimal LQG Control
Abed AlRahman Al Makdah, Vishaal Krishnan, Vaibhav Katewa +1
In this work, we revisit the Linear Quadratic Gaussian (LQG) optimal control problem from a behavioral perspective. Motivated by the suitability of behavioral models for data-drive…
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…
Learning Lipschitz Feedback Policies from Expert Demonstrations: Closed-Loop Guarantees, Generalization and Robustness
Abed AlRahman Al Makdah, Vishaal Krishnan, Fabio Pasqualetti
In this work, we propose a framework to learn feedback control policies with guarantees on closed-loop generalization and adversarial robustness. These policies are learned directl…
A Multiscale Analysis of Multi-Agent Coverage Control Algorithms
Vishaal Krishnan, Sonia Martínez
This paper presents a theoretical framework for the design and analysis of gradient descent-based algorithms for coverage control tasks involving robot swarms. We adopt a multiscal…
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…
Distributed Online Optimization for Multi-Agent Optimal Transport
Vishaal Krishnan, Sonia Martínez
We propose a scalable, distributed algorithm for the optimal transport of large-scale multi-agent systems. We formulate the problem as one of steering the collective towards a targ…
Identification of critical nodes in large-scale spatial networks
Vishaal Krishnan, Sonia Martínez
The notion of network connectivity is used to characterize the robustness and failure tolerance of networks, with high connectivity being a desirable feature. In this paper, we dev…
Distributed Control for Spatial Self-Organization of Multi-Agent Swarms
Vishaal Krishnan, Sonia Martínez
In this work, we design distributed control laws for spatial self-organization of multi-agent swarms in 1D and 2D spatial domains. The objective is to achieve a desired density dis…
Synchronization and semistability analysis of the Kuramoto model of coupled nonlinear oscillators
Vishaal Krishnan, Arun D. Mahindrakar, Somashekhar S. Hiremath
An interesting problem in synchronization is the study of coupled oscillators, wherein oscillators with different natural frequencies synchronize to a common frequency and equilibr…