Continuous-Time Identification using LQG-Balanced Model Reduction
Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
System identification of continuous-time model based on discrete-time data can be performed using a algorithm combining linear regression and LQG-balanced model reduction. The approach is applicable also to unstable system dynamics and it provides balanced models for optimal linear prediction and control.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Title of host publication||Proceedings of the 15th IFAC world congress|
|Publication status||Published - 2002|