A factorization-based framework for passivity-preserving model reduction of RLC systems

  • Authors:
  • Q. Su;V. Balakrishnan;C.-K. Koh

  • Affiliations:
  • Purdue University, West Lafayette, IN;Purdue University, West Lafayette, IN;Purdue University, West Lafayette, IN

  • Venue:
  • Proceedings of the 39th annual Design Automation Conference
  • Year:
  • 2002

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Abstract

We present a framework for passivity-preserving model reduction for RLC systems that includes, as a special case, the well-known PRIMA model reduction algorithm. This framework provides a new interpretation for PRIMA, and offers a qualitative explanation as to why PRIMA performs remarkably well in practice. In addition, the framework enables the derivation of new error bounds for PRIMA-like methods. We also show how the framework offers a systematic approach to computing reduced-order models that better approximate the original system than PRIMA, while still preserving passivity.