Muhammad Faisal Aftab

• Bounoua, Wahiba & Aftab, Muhammad Faisal (2024). Improved extended empirical wavelet transform for accurate multivariate oscillation detection and characterisation in plant-wide industrial control loops. Journal of Process Control. ISSN 0959-1524. 138. doi: 10.1016/j.jprocont.2024.103226.
• Darowski, Michal; Aftab, Muhammad Faisal; Li, Hongyu; Walker, David; Yu, Guoyu & An, Chenghui [Show all 7 contributors for this article] (2023). Towards Data-Driven Material Removal Rate Estimation in Bonnet Polishing. International Conference on Control, Mechatronics and Automation. ISSN 2837-5114. p. 473–479. doi: 10.1109/ICCMA59762.2023.10375024.
• Sterk-Hansen, Alexander; Saghaug, Bjørn; Hagen, Daniel & Aftab, Muhammad Faisal (2023). A ROS 2 and TwinCAT Based Digital Twin Framework for Mechatronics Systems. International Conference on Control, Mechatronics and Automation. ISSN 2837-5114. p. 485–490. doi: 10.1109/ICCMA59762.2023.10374978.
• Bounoua, Wahiba; Aftab, Muhammad Faisal & Omlin, Christian Walter Peter (2023). Stiction detection in industrial control valves using Poincaré plot-based convolutional neural networks. IFAC-PapersOnLine. ISSN 2405-8963. 56(2), p. 11687–11692. doi: 10.1016/j.ifacol.2023.10.523.
• Bounoua, Wahiba; Aftab, Muhammad Faisal & Omlin, Christian Walter Peter (2023). Online detrended fluctuation analysis and improved empirical wavelet transform for real-time oscillations detection in industrial control loops. Computers and Chemical Engineering. ISSN 0098-1354. 172. doi: 10.1016/j.compchemeng.2023.108173. Show summary

  Detrended Fluctuation Analysis (DFA) is a reliable and assumption-free approach for gauging the complexity of a time series. In this paper, an online oscillations detection paradigm is presented, which integrates the potential of DFA in detecting abnormal coherent fluctuations with the Empirical Wavelet Transform (EWT) efficiency in extracting the characteristics of oscillations. However, the standard EWT fails to separate modes oscillating at close frequencies, resulting in an incorrect decomposition. Furthermore, the lack of an appropriate stopping criterion frequently results in the signal being over-decomposed into several inconsequential components. Therefore, owing to the capability of DFA to differentiate between fluctuations stemming from noise and coherent fluctuations arising from genuine oscillations, an Improved EWT (IEWT) is presented to mitigate these issues and accurately extract only compelling oscillating modes. The proposed DFA-based IEWT framework is verified on simulated applications and data from real industrial processes, illustrating its effectiveness.

• Bounoua, Wahiba; Aftab, Muhammad Faisal & Omlin, Christian Walter Peter (2022). Controller performance monitoring: A survey of problems and a review of approaches from a data-driven perspective with a focus on oscillations detection and diagnosis. Industrial & Engineering Chemistry Research. ISSN 0888-5885. 61(49), p. 17735–17765. doi: 10.1021/acs.iecr.2c02785. Show summary

  Optimal operations of industrial control systems require rigorous monitoring to ensure safety, increase profitability, and minimize plant maintenance downtime. Thus, controller performance monitoring has been actively pursued by the research community, resulting in increased research publications over the past two decades. The availability of large data sets, the so-called big data era, has led impetus to the data-driven domain of controller performance monitoring. In this paper, a comprehensive review of the data-driven research in the CPM domain is presented. To illustrate the rationale behind the research efforts, a succinct explanation of the faults observed in control loops and their influence on overall controller performance is also presented. The paper then provides the publicly available data repositories adopted by most researchers to assess and compare their performance monitoring techniques realistically. Moreover, a review of the most eminent techniques proposed so far concerning both detection and diagnosis phases is presented.

• Bukhari, Syeda Halima Zahra; Hovd, Morten; Aftab, Muhammad Faisal & Winkler, Jan (2021). Design of parallel compensator and stabilizing controller to mitigate non-minimum phase behaviour of the Czochralski process. IFAC-PapersOnLine. ISSN 2405-8963. 53(2), p. 11710–11715. doi: 10.1016/j.ifacol.2020.12.669. Full text in Research Archive
• Khan, Muhammad Arshad; Aftab, Muhammad Faisal; Ahmad, Ejaz & Youn, Iljoong (2019). Active steering control system for an independent wheel drive electric vehicle. International Journal of Vehicle Design. ISSN 0143-3369. 79(4), p. 273–291. doi: 10.1504/IJVD.2019.103597.
• Aftab, Muhammad Faisal; Hovd, Morten & Sivalingam, Selvanathan (2019). Diagnosis of plant-wide oscillations by combining multivariate empirical mode decomposition and delay vector variance. Journal of Process Control. ISSN 0959-1524. 83, p. 177–186. doi: 10.1016/j.jprocont.2019.01.001.
• Khan, Muhammad Arshad; Aftab, Muhammad Faisal; Ahmed, Ejaz & Youn, Iljoong (2019). Robust Differential Steering Control System for an Independent Four Wheel Drive Electric Vehicle. International Journal of Automotive Technology. ISSN 1229-9138. 20(1), p. 87–97. doi: 10.1007/s12239-019-0008-9.
• Kölle, Konstanze; Aftab, Muhammad Faisal; Andersson, Leif Erik; Fougner, Anders Lyngvi & Stavdahl, Øyvind (2019). Data driven filtering of bowel sounds using multivariate empirical mode decomposition. Biomedical engineering online. ISSN 1475-925X. 18(28), p. 1–20. doi: 10.1186/s12938-019-0646-1. Full text in Research Archive
• Aftab, Muhammad Faisal; Hovd, Morten & Sivalingam, Selvanathan (2018). Improved oscillation detection via noise-assisted data analysis. Control Engineering Practice. ISSN 0967-0661. 81, p. 162–171. doi: 10.1016/j.conengprac.2018.08.019. Full text in Research Archive
• Andersson, Leif Erik; Scibilia, Francesco; Copland, Luke; Aftab, Muhammad Faisal & Imsland, Lars Struen (2018). Analysis of Iceberg Drift Trajectories Using the Multivariate Empirical Mode Decomposition . ISOPE - International Offshore and Polar Engineering Conference. Proceedings. ISSN 1098-6189. 2018-June, p. 1653–1660. doi: 10.1109/ccta.2017.8062605. Full text in Research Archive
• Aftab, Muhammad Faisal; Hovd, Morten & Sivalingam, Selvanathan (2018). Plant-wide oscillation detection using multivariate empirical mode decomposition. Computers and Chemical Engineering. ISSN 0098-1354. 117, p. 320–330. doi: 10.1016/j.compchemeng.2018.06.007. Full text in Research Archive
• Aftab, Muhammad Faisal; Hovd, Morten & Sivalingam, Selvanathan (2017). A Delay Vector Variance based Approach for Detecting and Isolating the Non-linearity Induced Oscillations in Control Loops. IFAC-PapersOnLine. ISSN 2405-8963. 50(1), p. 7975–7980. doi: 10.1016/j.ifacol.2017.08.992. Full text in Research Archive
• Andersson, Leif Erik; Aftab, Muhammad Faisal; Scibilia, Francesco & Imsland, Lars Struen (2017). Forecasting using multivariate empirical mode decomposition — Applied to iceberg drift forecast, 2017 IEEE Conference on Control Technology and Applications (CCTA). IEEE conference proceedings. ISSN 978-1-5090-2182-6. p. 1097–1103. doi: 10.1109/CCTA.2017.8062605.
• Bukhari, Halima Zahra; Aftab, Muhammad Faisal; Winkler, Jan & Hovd, Morten (2017). Adaptive Nonlinear Control of the Czochralski Process Via Integration of Second Order Sliding Mode and Iterative Learning Control. In Mareels, Iven & Tan, Ying (Ed.), Proceedings of the 2017 Asian Control Conference. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-5090-1572-6. p. 2732–2737. doi: 10.1109/ASCC.2017.8287609. Full text in Research Archive
• Aftab, Muhammad Faisal; Hovd, Morten & Sivalingam, Selvanathan (2017). Convergent cross mapping (CCM) based approach for isolating the source of plant-wide disturbances, 2017 IEEE Conference on Control Technology and Applications (CCTA). IEEE conference proceedings. ISSN 978-1-5090-2182-6. p. 1492–1498. doi: 10.1109/CCTA.2017.8062669. Full text in Research Archive
• Aftab, Muhammad Faisal; Hovd, Morten & Sivalingam, Selvanathan (2017). Detecting non-linearity induced oscillations via the dyadic filter bank property of multivariate empirical mode decomposition. Journal of Process Control. ISSN 0959-1524. 60, p. 68–81. doi: 10.1016/j.jprocont.2017.08.005. Full text in Research Archive
• Aftab, Muhammad Faisal; Hovd, Morten; Huang, Norden E & Sivalingam, Selvanathan (2016). An Adaptive Non-Linearity Detection Algorithm for Process Control Loops. IFAC-PapersOnLine. ISSN 2405-8963. 49(7), p. 1020–1025. doi: 10.1016/j.ifacol.2016.07.336. Full text in Research Archive

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• Andersson, Leif Erik; Scibilia, Francesco; Copland, Luke; Aftab, Muhammad Faisal & Imsland, Lars Struen (2018). Analysis of Iceberg Drift Trajectories Using the Multivariate Empirical Mode Decomposition - presentation .
• Andersson, Leif Erik; Aftab, Muhammad Faisal; Scibilia, Francesco & Imsland, Lars Struen (2017). Forecasting using multivariate empirical mode decomposition — Applied to iceberg drift forecast - presentation.
• Aftab, Muhammad Faisal; Hovd, Morten & Sivalingam, Selvanathan (2017). Convergent cross mapping (CCM) based approach for isolating the source of plant-wide disturbances.
• Bukhari, Halima Zahra; Aftab, Muhammad Faisal; Hovd, Morten & Winkler, Jan (2017). Adaptive Nonlinear Control of the Czochralski Process Via Integration of Second Order Sliding Mode and Iterative Learning Control.

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