3 citations · 5 across the 8 of their papers we have counts for
7 papers · 1 filter
An Innovations-Based Data-Driven Kalman Predictor for Predictive Control
Mohamed Abdalmoaty, Roy S. Smith
A recently developed data-driven Kalman filter requires offline measurement of the process disturbance; a requirement that is often unmet for many practical applications. We propos…
Ultrafast Grid Impedance Identification in -Asymmetric Three-Phase Power Systems
Mohamed Abdalmoaty, Verena Häberle, Xiuqiang He +1
We propose a non-parametric frequency-domain method to identify small-signal -asymmetric grid impedances, over a wide frequency band, using grid-connected converters. Existing…
Finite Sample Frequency Domain Identification
Anastasios Tsiamis, Mohamed Abdalmoaty, Roy S. Smith +1
We study non-parametric frequency-domain system identification from a finite-sample perspective. We assume an open loop scenario where the excitation input is periodic and consider…
Optimal Data-Driven Prediction and Predictive Control using Signal Matrix Models
Roy S. Smith, Mohamed Abdalmoaty, Mingzhou Yin
Data-driven control uses a past signal trajectory to characterise the input-output behaviour of a system. Willems' lemma provides a data-based prediction model allowing a control d…
Small Noise Analysis of Non-Parametric Closed-Loop Identification
Mohamed Abdalmoaty, Roy S. Smith
We revisit the problem of non-parametric closed-loop identification in frequency domain; we give a brief survey of the literature and provide a small noise analysis of the direct,…
Frequency-Domain Identification of Discrete-Time Systems using Sum-of-Rational Optimization
Mohamed Abdalmoaty, Jared Miller, Mingzhou Yin +1
We propose a computationally tractable method for the identification of stable canonical discrete-time rational transfer function models, using frequency domain data. The problem i…
Privacy and Security in Network Controlled Systems via Dynamic Masking
Mohamed Abdalmoaty, Sribalaji C. Anand, André M. H. Teixeira
In this paper, we propose a new architecture to enhance the privacy and security of networked control systems against malicious adversaries. We consider an adversary which first le…