Title :
A method of optimal system identification with applications in control
Author_Institution :
Dept. of Electr. Eng., Eindhoven Univ. of Technol., Netherlands
Abstract :
In this paper an optimal deterministic identification problem is solved in which a new measure for the misfit between data and system is minimized. It is shown that the misfit can be expressed as the Hankel norm of a specific operator. Optimal autonomous models are obtained by factorizing an optimal Hankel norm approximant of the Laplace transformed data matrix. An upper bound on the misfit between model and data is derived for a class of non-autonomous models of prescribed complexity. The identified autonomous systems are viewed as closed-loop behaviors of a feedback interconnection of two systems. Stability of these feedback interconnections is discussed
Keywords :
Hankel matrices; closed loop systems; feedback; identification; linear systems; optimisation; stability; time series; Hankel norm approximant; Laplace transformed data matrix; autonomous systems; closed-loop systems; deterministic identification; feedback interconnection; linear systems; optimal autonomous models; stabilisation; system identification; time series; upper bound; Context modeling; Control systems; Feedback; Linear systems; Mathematical model; Optimal control; Stability; State-space methods; System identification; Uncertainty;
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
DOI :
10.1109/CDC.1994.411358
