The conventional sensitivity analysis based on model-order reduction (MOR) techniques guarantees the passivity and, consequently, the stability of the reduced sensitivity circuit provided that the original circuit is passive. This excludes a large class of circuits that are stable but not necessarily passive. In this article, an efficient MOR method is presented for the sensitivity analysis of active stable circuits. The proposed algorithm preserves the stability of both the original and associated sensitivity equations, and is based on reducing the first-order variational equations in the form of a set of stable multi-input differential equations. The sensitivity equations are decomposed into several subsystems of equations where each subsystem contains a dedicated cluster of inputs, thereby avoiding the significant increase in the size of the reduced model due to increasing the number of inputs.

Additional Metadata
Keywords Active circuits, clustering, decomposition, model-order reduction (MOR), projection-based reduction methods, stability preservation, time-domain sensitivity
Persistent URL dx.doi.org/10.1109/TCPMT.2019.2933799
Journal IEEE Transactions on Components, Packaging and Manufacturing Technology
Citation
Nouri, B. (Behzad), & Nakhla, M.S. (2019). Efficient Time-Domain Sensitivity Analysis of Active Networks. IEEE Transactions on Components, Packaging and Manufacturing Technology, 9(9), 1721–1729. doi:10.1109/TCPMT.2019.2933799