Evolutionary Based Controller Design
Created by W.Langdon from
gp-bibliography.bib Revision:1.8229
- @InCollection{Sekaj:2009:EC,
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title = "Evolutionary Based Controller Design",
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author = "Ivan Sekaj",
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booktitle = "Evolutionary Computation",
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publisher = "InTech",
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year = "2009",
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editor = "Wellington Pinheiro dos Santos",
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chapter = "13",
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month = oct,
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-953-307-008-7",
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URL = "
http://www.intechopen.com/download/pdf/pdfs_id/10935",
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DOI = "
DOI:10.5772/9620",
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bibsource = "OAI-PMH server at www.intechopen.com",
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language = "eng",
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oai = "oai:intechopen.com:10935",
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URL = "
http://www.intechopen.com/articles/show/title/evolutionary-based-controller-design",
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abstract = "In this chapter evolutionary based design/optimisation
approaches has been proposed for controller design of
continuous-time process control. Parameters of
controllers with fixed defined internal structure are
designed as well as controllers with a-priori unknown
internal structure and its parameters. The presented
approaches minimise a cost function, which comprises
closed-loop system simulation and performance index
evaluation. In this way the controller design is
transformed into a search problem in the n-dimensional
parameter space. The design/optimisation can be carried
out for complex systems and control structures of
various types. The main and practically the only
limitation of the approach is the time consuming
computation (compared with conventional approaches) due
to thousands up to ten thousands closed-loop
simulations needed by each design procedure. From the
point of view the user, on the other hand, the design
method is simple to use. It transfers the design effort
from the experienced human designer to the computer.
The design approach is simple to extend to robust
controller design, for which two different methods have
been proposed. In addition statistical robustness
measure has been introduced, which can be considered as
an objective tool for robust controller performance
comparison. Next, the design idea has been extended
also to a multi-objective design task, where the
objective is the search for the Pareto-optimal set of
solutions. From these solutions the designer can choose
the representative, which is the most appropriate in
the particular case. Finally the design goal was
extended from a fix defined controller structure with
unknown controller parameters to the
search/optimisation of the unknown internal structure
of the controller. From that reason, the Genetic
Programming has been used. The proposed
evolutionary-based methods can be used for design of
various types of controllers for various system types
(linear, non-linear, stable, unstable, SISO and MIMO,
fuzzy, neural, etc.). The only condition of this
approach is that there exists a simulation model of the
designed closed-loop. In the future, this design
approach will be extended for solving very complex
design tasks in the process control area like complex
MIMO control systems for non-linear continuous-time
systems and for robotic applications using parallel
evolutionary algorithms.",
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size = "22 pages",
- }
Genetic Programming entries for
Ivan Sekaj
Citations