Validation of Control Software and Benchmarking
Control Software and Benchmarking
In the analysis of numerical methods and their
implementation as numerical software it is extremely important to be able to test the
correctness of the implementation as well as the performance of the method. This
validation is one of the major steps in the construction of a software library, in
particular if this library is used in practical applications.
In order to carry out such a test it is important to
have tools that yield an evaluation of the performance of the method as well as the
implementation with respect to correctness, accuracy and speed. Similar tools are needed
to be able to compare different numerical methods, to test their robustness, and also to
analyse the behaviour of the methods in extreme situation, i.e., on problems where the
limit of the possible accuracy is reached.
In many application areas therefore benchmark
collections have been created that can partially serve for this purpose. Such collections
are heavily used. In our opinion, in order to have a fair evaluation and a comparison of
methods and software, there should be a standardized set of examples on which newly
developed methods and their implementation can be tested. It
was one of the goals of WGS to create such
testing and validation environments for the area of numerical methods in control, in
particular it was planned to accompany the SLICOT library with
benchmark collections for each of the major problem areas. In order to make such
collections useful, it is important that they cover a wide range of problems and
also problems difficult to solve in finite arithmetic are included. Such problems
in particular drive the methods and their implementation to a limit. These are ideal test
cases, since errors and failures usually occur only in extreme cases and these are often
not covered by standard software validation procedures.
The SLICOT library
currently contains such benchmark collections for:
- standard and generalized continuous-time and discrete-time systems models
(see reports 2 and 3)
- continuous-time and discrete-time standard and generalized Lyapunov matrix
equations (see reports 4 and 5)
- continuous-time and discrete-time algebraic Riccati matrix equations
(see reports 6 and 7)
- identification (see report 8)
- model reduction of (high order) linear time invariant dynamical systems
containing some useful "real world" examples reflecting current
problems in applications can be found here
(see also report 9)
Everybody is invited to submit such benchmark
examples for the SLICOT benchmark collection. For submissions please contact Prof. Volker Mehrmann.
Available Reports
1. Volker Mehrmann and Thilo Penzl: Benchmark
collections in SLICOT SLICOT Working Note 1998-5, June 1998.
2. Daniel Kressner, Volker Mehrmann and Thilo Penzl: DTDSX -
A collection of benchmark examples for state-space realizations of
time-invariant discrete-time systems;
SLICOT Working Note 1998-10: November 1998, revised June 1999.
3. Daniel Kressner, Volker Mehrmann and Thilo Penzl: CTDSX -
A collection of benchmark examples for state-space realizations of
time-invariant continuous-time systems; SLICOT Working Note 1998-9: November 1998.
4. Daniel Kressner, Volker Mehrmann and Thilo Penzl: DTLEX -
A collection of benchmark examples for discrete-time Lyapunuv equations;
SLICOT Working Note 1999-7: June 1999.
5. Daniel Kressner, Volker Mehrmann and Thilo Penzl: CTLEX -
A collection of benchmark examples for continuous-time Lyapunuv equations;
SLICOT Working Note 1999-6: June 1999.
6. Jörn Abels and Peter Benner: DAREX - A
collection of benchmark examples for discrete-time algebraic Riccati equations (version 2.0);
SLICOT Working Note 1999-16: December 1999. 7.
Jörn Abels and Peter Benner: CAREX -
A collection of benchmark examples for continuous-time algebraic Riccati equations (version 2.0);
SLICOT Working Note 1999-14: December 1999.
8. Ad van den Boom, Ton Backx and Yucai Zhu: Benchmarks
for identification; NICONET Report 1999-19: July 2000.
9. Younès Chahlaoui and Paul Van Dooren: A
collection of benchmark examples for model reduction of linear time invariant
dynamical systems; SLICOT Working Note 2002-2: February 2002.
Some Matrix Collections Suitable for Benchmarking:
Ad van den Boom, March 4, 2002
Updated: Vasile
Sima, August 31, 2005; June 15, 2006; June 8, 2009
|