MODEL ORDER REDUCTION OF ELECTRICAL CIRCUITS: A COMPARATIVE STUDY OF POSITIVE-REAL BALANCED TRUNCATION AND ITERATIVE RATIONAL KRYLOV

Abstract

Model Order Reduction (MOR) is for simplifying complex electrical, electronic circuit models while preserving essential system characteristics. This study compares two MOR algorithms: Positive-Real Balanced Truncation (PRBT) and the Iterative Rational Krylov Algorithm (IRKA). The PRBT approach involves the determination of controller and observer Gramians through the solution of Riccati equations, enabling the preservation of stability and passivity properties. The IRKA employs an iterative of interpolation points to converge towards an optimal reduced-order approximation. The performance of these algorithms is evaluated through the implementation of an RLC circuit model in MATLAB software. The results encompass error analysis, comparisons of impulse response, magnitude response, and phase response according to frequency between the original and reduced-order systems. The strengths and limitations of each method, providing into their applicability involving model order reduction of electrical circuits. By considering factors such as accuracy, computational complexity, and preservation of system properties, we can make decisions regarding the selection of MOR algorithms for specific circuit modeling tasks. This study contributes to the ongoing advancement of MOR techniques in electrical engineering, facilitating the development of efficient and accurate application circuit models.