FSID - A Frequency Weighted MIMO Frequency Domain Identification and Rational Matrix Approximation Method for Python, Julia and Matlab
Paper in proceeding, 2021

An open source toolbox, FSID, implemented in the Python, Julia and MATLAB programming languages is described. The toolbox provides scripts which estimates linear multiinput multi-output state-space models from sample data using frequency-domain subspace algorithms. Algorithms which estimate models based on samples of the transfer function matrix as well as frequency domain input and output vectors are provided. The algorithms can be used for discrete-time models, continuous-time models as well as for approximation of rational matrices from samples corresponding to arbitrary points in the complex plane. The algorithms can handle frequency dependent weighting which enable to obtain approximate BLUE estimates. To reduce the computational complexity for the estimation algorithms, an accelerated algorithm is provided which evaluate the state-space realization of the transfer function matrix at arbitrary points.

Subspace methods

Frequency domain identification

Software for system identification

Continuous time system estimation

Author

Tomas McKelvey

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

M. Gibanica

Volvo Cars

IFAC-PapersOnLine

2405-8963 (ISSN)

Vol. 54 7 403-408

19th IFAC Symposium on System Identification (SYSID)
Padova, Italy,

Subject Categories

Probability Theory and Statistics

Control Engineering

Signal Processing

DOI

10.1016/j.ifacol.2021.08.393

More information

Latest update

11/15/2021