Towards D-Optimal Input Design for Finite-Sample System Identification
نویسندگان
چکیده
منابع مشابه
Optimal input design for system identification using spectral decomposition
The aim of this paper is to design a band-limited optimal input with power constraints for identifying a linear multi-input multi-output system. It is assumed that the nominal system parameters are specified. The key idea is to use the spectral decomposition theorem and write the power spectrum as φu(jω) = 1 2 H(jω)H∗(jω). The matrix H(jω) is expressed in terms of a truncated basis for L ([−ωcu...
متن کاملFinite-Horizon Input Selection for System Identification∗
The accuracy of an identified model depends on the choice of input signal. Persistency of excitation is a necessary criterion for such signals. In this paper we develop additional criteria for input signal selection, in particular, the input at each time step is chosen to minimize the predicted variance of the system estimate at the next time step. We extend the method to the finitehorizon inpu...
متن کاملOn the Design of Optimal Input Signals in System Identification
The problem of designing optimal inputs in the identification of linear systems with unknown random parameters is considered using a Bayesian approach. The information matrix, which is positive definite for the class of systems analyzed, gives a measure of performance for the system inputs. The computation of the optimal closed-loop input mappings is shown to be a nontrivial exercise in adaptiv...
متن کاملFinite sample properties of system identification methods
In this note, we study the quality of system identification models obtained using the standard quadratic prediction error criterion for a general linear model class. The main feature of our results is that they hold true for a finite data sample and they are not asymptotic. The main theorems bound the difference between the expected value of the identification criterion evaluated at the estimat...
متن کاملOptimal Input Design for Subspace-Based Fault Detection and Identification
This study focuses on input design for subspace based fault detection and identification methods and investigates its possible advantages over using noise inputs. In several real applications the noise available in environment is the only input to the system and in some cases produce low quality output data for subspace identification and fault detection purposes. Therefore, model order may be ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2018
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2018.09.136