Search Results for author: Ratnesh Kumar

Found 10 papers, 2 papers with code

Dynamic Calibration of Nonlinear Sensors with Time-Drifts and Delays by Bayesian Inference

no code implementations29 Aug 2022 Soumyabrata Talukder, Souvik Kundu, Ratnesh Kumar

Most sensor calibrations rely on the linearity and steadiness of their response characteristics, but practical sensors are nonlinear, and their response drifts with time, restricting their choices for adoption.

Bayesian Inference

Data-Driven Linear Koopman Embedding for Networked Systems: Model-Predictive Grid Control

no code implementations2 Jun 2022 Ramij R. Hossain, Rahmat Adesunkanmi, Ratnesh Kumar

This paper presents a data-learned linear Koopman embedding of nonlinear networked dynamics and uses it to enable real-time model predictive emergency voltage control in a power network.

Model Predictive Control

Distributed-MPC with Data-Driven Estimation of Bus Admittance Matrix in Voltage Control

no code implementations28 Feb 2022 Ramij R. Hossain, Ratnesh Kumar

This article presents a distributed model-predictive control (MPC) design for real-time voltage control in power systems, including an online method to estimate the bus admittance matrix $\mathbf{Y}$ to let it be time-varying and unknown a priori.

Anomaly Detection Distributed Optimization +1

Expectation Distance-based Distributional Clustering for Noise-Robustness

no code implementations17 Oct 2021 Rahmat Adesunkanmi, Ratnesh Kumar

This paper presents a clustering technique that reduces the susceptibility to data noise by learning and clustering the data-distribution and then assigning the data to the cluster of its distribution.

Clustering

Robust Stability of Neural Network-controlled Nonlinear Systems with Parametric Variability

no code implementations13 Sep 2021 Soumyabrata Talukder, Ratnesh Kumar

To develop a general theory for stability and stabilizability of a neural network (NN)-controlled nonlinear system subject to bounded parametric variation, a Lyapunov-based stability certificate is proposed and is further used to devise a maximal Lipschitz bound for the NN controller, and also a corresponding maximal region-of-attraction (RoA) inside a given safe operating domain.

MPC-based Realtime Power System Control with DNN-based Prediction/Sensitivity-Estimation

no code implementations5 Jun 2021 Ramij Raja Hossain, Ratnesh Kumar

This paper presents a model predictive control (MPC)-based online real-time adaptive control scheme for emergency voltage control in power systems.

Model Predictive Control

Vehicle Re-Identification: an Efficient Baseline Using Triplet Embedding

no code implementations4 Jan 2019 Ratnesh Kumar, Edwin Weill, Farzin Aghdasi, Parthsarathy Sriram

In this paper we provide an extensive evaluation of these losses applied to vehicle re-identification and demonstrate that using the best practices for learning embeddings outperform most of the previous approaches proposed in the vehicle re-identification literature.

Vehicle Re-Identification

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