System Identification
System Identification covers a very wide range of techniques for obtaining
a system model from inputs and outputs to the system. They can be classed
into parametric (e.g. Recursive Least Squares) or non-parametric (e.g.
frequency testing).
Recursive Least Squares
Pseudo-Random Binary Sequence (PRBS)
Articles on System Identification
Internet Resources on Identification
Commercial Companies
Recursive Least Squares
- Here's a simle Matlab script for SISO
RLS - it will need some modification to be embedded within
your own code. But the basics are all there. There are three RLS
algorithms available. A MIMO script is also available, as are
'C' code modules for the above.
Pseudo-Random Binary Sequence (PRBS)
-
Within Matlab/Simulink the only way to get a PRBS generating M-file is
within the Frequency Domain System Identification Toolbox (called mlbs
- Maximum Length Binary Sequence) or in the System Identification Toolbox
v4.0 (called idinput). Here's a simple Matlab script written by Rob Lynch
to do just that:-
Subject: Re: help.. how to generate a PRBS signal in Matlab??
Date: 1997/11/10
Author: Rob Lynch <lynch@accesscom.com>
Here is a simple program to generate pseudo-random bit sequences
(you can find polynomials for different-length PRBS' in, for example, Peterson
and Weldon, "Error-Correcting Codes" and many other books).
function z=prbs(init,g)
% z=prbs(init,g)
% 2^n-1-bit PRBS based on initial string 'init'
% and polynomial represented by vector g (e.g., g=[7 1] => x^7+x+1).
% Rob Lynch Quinta Corporation 3/31/97
z=init;
n=length(init);
for i=(n+1):(2^n-1)
q=z(i-g(1));
for j=2:length(g)
end
z=[z q];
end
Articles and Books on System Identification
- "Identification in Closed Loop : A Powerful Design Tool", I.D.Landau, IFAC Journal of Control
Engineering Practice, 2001.
Describes recent developments in closed loop system identification and how it can yield better, more
accurate models for controller design. Also presents robust controllers designed using such
identified models, for an experimental drive and flexible transmission system.
- "NNSYSID and NNCTRL: Tools for System Identification and Control with Neural Networks", M.Norgaard,
O.Ravn and N.K.Poulsen, IEE Computing & Control Journal, February 2001.
Describes two toolboxes for use with Matlab that give neural network system identification
and control design, including training algorithms, model validation and model structure selection. These
toolboxes are freely downloadable at nnsysid.html
and nnctrl.html.
- "Multivariable System Identification
for Process control", by Yucai Zhu, published by Elsevier Science Ltd, UK, Oct 2001.
372 pages, ISBN: 0-08-043985-3. Matlab software for this book are available for download.
-
"Interaction Between Identification and Robust Control", Paul van den Hof, Delf University of Technology
Internet Resources on Identification
Commercial Companies working in System Identification
-
Tai-Ji Control is a
control technology company specialized in industrial process identification.
It produces a package called Tai-Ji
ID for automatic closed-loop identification based on the ASYM method
of identification developed by Yucai Zhu.
- Adaptics Inc.
makers of ADAPTx an automated multivariable system identification and time series analysis software.
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