Convex Optimization In Identification Of Stable Non-Linear State Space Models

被引：26

作者：

Tobenkin, Mark M.

Manchester, Ian R.

Wang, Jennifer

Megretski, Alexandre

Tedrake, Russ

机构：

来源：

49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2010年

关键词：

D O I：

10.1109/CDC.2010.5718114

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state data, with a performance objective defined as a measure of robustness of the simulation error with respect to equation errors. Basic definitions and analytical results are presented. The utility of the method is illustrated on a simple simulation example as well as experimental recordings from a live neuron.

引用

页码：7232 / 7237

页数：6

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