Automatic Synthesis of Microcontroller Assembly Code Through Linear Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7975
- @InCollection{MotaDias:2006:GSP,
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author = "Douglas {Mota Dias} and
Marco Aur\'{e}lio C. Pacheco and Jos\'{e} F. M. Amaral",
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title = "Automatic Synthesis of Microcontroller Assembly Code
Through Linear Genetic Programming",
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year = "2006",
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booktitle = "Genetic Systems Programming: Theory and Experiences",
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pages = "193--227",
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volume = "13",
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series = "Studies in Computational Intelligence",
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editor = "Nadia Nedjah and Ajith Abraham and
Luiza {de Macedo Mourelle}",
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publisher = "Springer",
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address = "Germany",
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keywords = "genetic algorithms, genetic programming, control",
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ISBN = "3-540-29849-5",
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DOI = "doi:10.1007/3-540-32498-4_9",
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abstract = "This chapter considers the application of linear
genetic programming in the automatic synthesis of
microcontroller assembly language programs that
implement strategies for time optimal or sub-optimal
control of the system to be controlled, based on
mathematical modelling through dynamic equations. One
of the difficulties presented by the conventional
design of optimal control systems lies in the fact that
solutions to problems of this type normally involve a
highly non-linear function of the system s state
variables. As a result, it is often not possible to
find an exact mathematical solution. As for the
implementation of the controller, there arises the
difficulty of programming the microcontroller manually
in order to execute the desired control. The research
that has been done in the area of automatic synthesis
of assembly language programs for microcontrollers
through genetic programming is surveyed in this chapter
and a novel methodology in which assembly language
programs are automatically synthesised, based on
mathematical modeling through dynamic plant equations,
is introduced. The methodology is evaluated in two case
studies: the cart-centering problem and the inverted
pendulum problem. The control performance of the
synthesised programs is compared with that of the
systems obtained by means of a tree-based genetic
programming method. The synthesised programs proved to
perform at least as well, but they had the additional
advantage of supplying the solution already in the
final format of the implementation platform selected: a
microcontroller.",
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notes = "http://www.springer.com/sgw/cda/frontpage/0,11855,5-146-22-92733168-0,00.html
Not Turing complete; no loops limited use of
memory???
Subset 22 (of 75) PIC18F452 implemented. MPLAB
simulator.",
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size = "35 pages",
- }
Genetic Programming entries for
Douglas Mota Dias
Marco Aurelio Cavalcanti Pacheco
Jose F M Amaral
Citations