DC-Centric Parameterized Reduced-Order Model via Moment-Based Interpolation Projection (MIP) Algorithm

This article presents a new approach to construct parameterized reduced-order models for nonlinear circuits. The reduced model is obtained such that it matches the variations in the DC operating point of the original full circuit in response to variations in several of its key design parameters. The new approach leverages, through the use of circuit moments with respect to the design parameters, the discrete empirical interpolation approach developed in a model reduction in other domains and enables its efficient application to the problem of DC operating point in nonlinear circuits. Utilizing the idea of rooted trees, the proposed approach constructs orthogonal bases that are used in projecting the full equations of the large original nonlinear circuit onto a reduced system of nonlinear equations in a space with a much smaller dimension. The variations in the DC operating point of the full circuit are then obtained by solving the reduced system of equations, yielding significant computational savings. Numerical examples are presented to demonstrate the efficiency and accuracy of the reduced model in predicting the change in the DC operating point of the original circuit.

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