HIT Toolbox
Bibliography.txt
in the root directory of HIT).
Its development has been supported by the EU projects HYGEIA and HYCON.
Download
16 Jan.2006: HIT 1.00  .zip package. Required software: MatLab >= 6.5.
Installation and first steps
HIT uses the Multi Parametric Toolbox (MPT) developed at ETH (Zurich, Switzerland) for handling polytopes and solving LP/QP problems.
From 06/12/2005, HIT is shipped as part of MPT, thus it is automatically installed if you download MPT >= 2.5.
For a standalone installation of HIT, unzip it and add its path (and the path of the subdirectories as well) to the matlabpath
.
Then, try out the examples in the /examples
directory. The code of the examples is well commented and you won't have any difficulty in adapting them for solving your problems.
In the /doc
directory there is the html documentation of HIT and a manual (in pdf).
Main features of HIT
 Clustering algorithms: weighted Kmeans and singlelinkage
 Pattern recognition algorithms:
 Linear Support Vector Classifiers (SVC)
 Multicategory Robust Linear Programmng (MRLP)
 Proximal Support Vector Classifiers (PSVC)
 Continuous and discontinuous PWA/PWARX models
 Postprocessing: optional reclassification of outliers
Problems solved by HIT

Regression problem: reconstruct a PWA map from noisy samples. In this case, one is not dealing with a dynamical system (with inputs and outputs) but just with a static map that is sampled. HIT returns a databased PWA approximation of the map (see the examples
ex_approx_1d.m
andex_cake1.m
.  the second example shows how to approximate discontinuous PWA maps). The approximation hasidmodes.s
modes (in HITs jargon, a "mode" is an affine hyperplane + the region where it is valid). 
Identification problem: reconstruct a PWARX hybrid system from noisy inputs and outputs (see for instance
ex_pwarx_2d_3modes.m
). PWARX systems are multiinput/singleoutput descriptions of hybrid systems. Thus no state appears. But they can be rewritten as PWA system pretty much the same way ARX models can be rewritten as linear systems in the statespace form.
The PWARX systems used in the HIT toolbox are in the form
y(k)=idmodes.par{i}* [x(k)' 1]' if x(k) \in \idmodes.regions(i)
wherex(k)=[y(k1) ... y(kna) u'(k1) ... u'(knb)]
is the vector of regressors and the integers na and nb are the system order. If you want to write a PWARX model in the PWA form you have to interpret x(k) as a state, y(k) as an output and find the matricesA_i
,b_i
,f_i
,C_i
,D_i
,g_i
that given a sequence u(k) produce the same output of the PWARX model.
Citation info
BibTeX entry:
 author = {G. FerrariTrecate},
 title = {{Hybrid Identification Toolbox (HIT)}},
 year = {2005},
 }
Acknowledgments
See the fileAcknowledgments.txt
in the root directory of HIT.