首页|A factorization-based framework for passivity-preserving model reduction of RLC systems
A factorization-based framework for passivity-preserving model reduction of RLC systems
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NETL
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。
passivity preserving
Q. Su、V. Balakrishnan、C.-K. Koh
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Purdue University, West Lafayette, IN
Conference on Design automation
New Orleans, LA(US)
Proceedings of the 39th conference on Design automation
NETL
