Home        
Research
Publications
Teaching
Links

Mohamed Rasheed-Hilmy Abdalmoaty

Submitted Manuscripts

  • M Abdalmoaty and R. Smith. Small Noise Analysis of Non-Parametric Closed-Loop Identification. Submitted for CDC 2024.

  • A. Tsiamis, M Abdalmoaty, R. Smith, J. Lygeros. Finite Sample Frequency Domain Identification. Submitted for CDC 2024.

  • R. Smith, M. Abdalmoaty, M. Yin. Optimal Data-Driven Prediction and Predictive Control using Signal Matrix Models. Submitted for CDC 2024.

  • R. Smith, M. Abdalmoaty, M. Yin. Data-driven formulation of the Kalman filter and its Application to Predictive Control. Submitted for CDC 2024.

Journal Articles

  • F. E. Tosun, A. M. H. Teixeira, M. Abdalmoaty, A. Ahlén, S. Dey. Quickest Detection of Bias Injection Attacks on the Glucose Sensor in the Artificial Pancreas Under Meal Disturbances. In Journal of Process Control, vol. 153, no. 103162, March 2024.

  • A. Ghosh, M. Abdalmoaty, S. Chatterjee, and H. Hjalmarsson. DeepBayes - an estimator for parameter estimation in stochastic nonlinear dynamical models. In Automatica 159 (2024): 111327.

  • D. Rodrigous, M. Abdalmoaty, E.W. Jacobsen, V. Chotteau, and H. Hjalmarsson. An Integrated Approach for Modeling and Identification of Perfusion Bioreactors via Basis Flux Modes. In Computers & Chemical Engineering (2021): 107238.

  • M. Abdalmoaty, H. Hjalmarsson, and B. Wahlberg. The Gaussian MLE Versus the Optimally Weighted LSE [Lecture Notes]. In IEEE Signal Processing Magazine, Volume 37, Issue 6, 2020.

  • M. Abdalmoaty and H. Hjalmarsson. Identification of Stochastic Nonlinear Models Using Optimal Estimating Functions. In Automatica 119 (2020): 109055.

  • M. Abdalmoaty and H. Hjalmarsson. Linear Prediction Error Methods for Stochastic Nonlinear Models. In Automatica 105 (2019): 49-63.

Conference Papers

  • M. Abdalmoaty, J. Miller, M. Yin, and R. Smith. Frequency-Domain Identification of Discrete-Time Systems using Sum-of-Rational Optimization. Accepted for IFAC Symposium on System Identification, Boston, USA.

  • M. Abdalmoaty, E. Balta, J. Lygeros, and R. Smith. Online Identification of Stochastic Continuous-Time Wiener Models Using Sampled Data. Accepted for ECC 2024 Stockholm, Sweden.

  • M. Abdalmoaty, Sribalaji C. Anand and André Teixeira. Privacy and Security in Network Controlled Systems via Dynamic Masking. In IFAC-PapersOnLine, Volume 56, Issue 2, pp. 991-996, 2023.

  • M. Abdalmoaty and A. Medvedev. Continuous-Time Pure Delay Estimation From Sampled Measurements. In IFAC-PapersOnLine, Volume 56, Issue 2, pp. 6982-6987, 2023.

  • M. Abdalmoaty and A. Medvedev. Noise reduction in Laguerre-domain discrete delay estimation. In the 61th IEEE Conference on Decision and Control (CDC2022).

  • R. Bereza, O. Eriksson, M. Abdalmoaty, D. Broman, and H. Hjalmarsson. Stochastic Approximation for Identification of Non-Linear Differential-Algebraic Equations with Process Disturbances. In the 61th IEEE Conference on Decision and Control (CDC).

  • M. Abdalmoaty and A. Medvedev. Noise reduction in Laguerre-domain discrete delay estimation. In the 61th IEEE Conference on Decision and Control (CDC).

  • A. Ghosh, A. Fontcuberta, M. Abdalmoaty, and S. Chatterjee. Time-Varying Normalizing Flows for Dynamical Signals. In the 30th European Signal Processing Conference (EUSIPCO 2022).

  • M. Abdalmoaty, O. Eriksson, R. Bereza, D. Broman, and H. Hjalmarsson. Identification of Non-Linear Differential-Algebraic Equation Models with Process Disturbances. In the 60th IEEE Conference on Decision and Control (CDC) July 2021.

  • D. Rodrigues, M. Abdalmoaty, and H. Hjalmarsson. Toward Tractable Global Solutions to Bayesian Point Estimation Problems via Sparse Sum-of-Squares Relaxations. In the 2020 American Control Conference (ACC), pp. 1501-1506.

  • D. Rodrigues, M. Abdalmoaty, and H. Hjalmarsson. Toward Tractable Global Solutions to Maximum-Likelihood Estimation Problems via Sparse Sum-of-Squares Relaxations. In the 58th IEEE Conference on Decision and Control (CDC),pp. 3184-3189, 2019.

  • M. Abdalmoaty and H. Hjalmarsson. Consistent estimators of stochastic MIMO Wiener models based on suboptimal predictors. In the 57th IEEE Conference on Decision and Control (CDC), pp. 3842-3847, 2018.

  • M. Abdalmoaty and H. Hjalmarsson. Application of a linear PEM estimator to a stochastic Wiener-Hammerstein benchmark problem. In IFAC-PapersOnLine, Volume 51, Issue 15, pp. 784-789, 2018.

  • M. Abdalmoaty, C. R. Rojas, and H. Hjalmarsson. Identification of a class of nonlinear dynamical networks. In IFAC-PapersOnLine, Volume 51, Issue 15, pp. 868-873, 2018.

  • M. Abdalmoaty and H. Hjalmarsson. Simulated pseudo maximum likelihood identification of nonlinear models. In IFAC-PapersOnLine, Volume 50, Issue 1, pp. 14058-14063, 2017.

  • M. Abdalmoaty and H. Hjalmarsson. A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems. In the 55th IEEE Conference on Decision and Control (CDC), pp. 3060-3065, 2016.

  • M. Abdalmoaty and H. Hjalmarsson. On Re-weighting, Regularization Selection, and Transient in Nuclear Norm based Identification. In IFAC-PapersOnLine, Volume 48, Issue 28, pp. 092-097, 2015.

  • M. Abdalmoaty, D. Henrion and L. Rodrigues. Measures and LMIs for optimal control of piecewise-affine systems. European Control Conference, Zurich 2013.

Theses

  • M. Abdalmoaty. Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions. KTH Royal Institute of Technology, TRITA-EECS-AVL-2019:63, ISBN 978-91-7873-267-8, 2019.

  • M. Abdalmoaty. Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors. KTH Royal Institute of Technology, TRITA-EE 2017:172, ISBN 978-91-7729-624-9, 2017.

  • M. Abdalmoaty. Measures and LMIs for Optimal Control of Piecewise-Affine Dynamical Systems: Systematic feedback synthesis in continuous-time. Luleå University of Technology, 2012.