Abstract
In the domain of electrical and electronic engineering, managing the complexity of systems with numerous components presents challenges in analysis, simulation, and control. Model Order Reduction (MOR) techniques provide a solution by creating simplified models while retaining system behavior. This study investigates two widely-used MOR algorithms: Positive-Real Truncated Balanced Realization (PRR) and Proper Orthogonal Decomposition (PODA). We apply these methods to an 8th-order electrical circuit and compare their performance in reducing system order. Through comprehensive analysis, we demonstrate that while PRR exhibits sensitivity to dimension choices and accuracy limitations, PODA consistently maintains accuracy across various reduced dimensions. Our findings emphasize PODA's robustness and suitability for accurate model order reduction, particularly in time-domain applications. This research contributes insights into selecting appropriate MOR techniques based on application demands and underscores the significance of advanced MOR methods in addressing system complexity challenges.
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This research result is the product of a university-level scientific research project with code ĐH2023-TN07-01, funded by the Thai Nguyen University of Information and Communication Technology (ICTU).
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Nguyen, TT., Dao, HD., Vu, NK. (2023). Comparative Evaluation of PRR and PODA Methods for Model Order Reduction in Electrical Circuits. In: Nghia, P.T., Thai, V.D., Thuy, N.T., Son, L.H., Huynh, VN. (eds) Advances in Information and Communication Technology. ICTA 2023. Lecture Notes in Networks and Systems, vol 847. Springer, Cham. https://doi.org/10.1007/978-3-031-49529-8_25
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DOI: https://doi.org/10.1007/978-3-031-49529-8_25
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