Time complexity and model complexity of fast identification of continuous-time LTI systems

作     者：Lin, L Wang, LY Zames, G 

作者机构：MPD Technol Inc Hauppauge NY 11788 USA Wayne State Univ Dept Elect & Comp Engn Detroit MI 48202 USA 

出 版 物：《IEEE TRANSACTIONS ON AUTOMATIC CONTROL》 (IEEE Trans Autom Control)

年 卷 期：1999年第44卷第10期

页      面：1814-1828页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0811[工学-控制科学与工程] 

主　　题：adaptive control H-infinity identification model complexity time complexity 

摘      要：The problem of fast identification of continuous-time systems is formulated in the metric complexity theory setting. It is shown that the two key steps to achieving fast identification, i.e., optimal input design and optimal model selection, can be carried out independently when the true system belongs to a general a priori set. These two optimization problems can be reduced to standard Gel fand and Kolmogorov n-width problems in metric complexity theory. It is shown that although arbitrarily accurate identification can be achieved on a small time interval by reducing the noise-signal ratio and designing the input carefully, identification speed is limited by the metric complexity of the a priori uncertainty set when the noise/signal ratio is fixed.