Automatic Synthesis of Digital Microcontroller programs by Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Douglas {Mota Dias}",
  title =        "Automatic Synthesis of Digital Microcontroller
                 programs by Genetic Programming",
  school =       "Engenharia Eletrica, Pontificia Universidade Catolica
                 do Rio de Janeiro - PUC-Rio",
  year =         "2005",
  type =         "Masters",
  address =      "Brasil",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  DOI =          "doi:10.17771/PUCRio.acad.6666",
  abstract =     "the use of genetic programming in automatic synthesis
                 of assembly language programs for microcontrollers,
                 which implement time-optimal or sub-optimal control
                 strategies of the system to be controlled, from the
                 mathematical modelling by dynamic equations. One of the
                 issues faced in conventional design of an optimal
                 control system is that solutions for this kind of
                 problem commonly involve a highly nonlinear function of
                 the state variables of the system. As a result,
                 frequently it is not possible to find an exact
                 mathematical solution. On the implementation side, the
                 difficulty comes when one has to manually program the
                 microcontroller to run the desired control. Thus, the
                 objective of this work was to overcome these
                 difficulties applying a methodology that, starting from
                 the mathematical modeling of a plant, provides as
                 result an assembly language microcontroller program.
                 The work included a study of the possible types of
                 genetic representation for the manipulation of assembly
                 language programs. In this regard, it has been
                 concluded that the linear is the most suitable
                 representation. The work also included the
                 implementation of a tool to accomplish three study
                 cases: water bath, cart centering and inverted
                 pendulum. The performance of control of the synthesised
                 programs was compared with the one obtained by other
                 methods (neural networks, fuzzy logic, neurofuzzy
                 systems and genetic programming). The synthesized
                 programs achieved at least the same performance of the
                 other systems, with the additional advantage of already
                 providing the solution in the final format of the
                 chosen implementation platform: a microcontroller.",
  notes =        "the Digital Library of Maxwell System

                 Collaborator(s): MARCO AURELIO C PACHECO - MPACHECO -
                 ADVISOR More Information

                 Input Date: 28/06/2005

                 Document Language: PORTUGUESE - BR

                 See also \cite{MotaDias:2006:GSP}",

Genetic Programming entries for Douglas Mota Dias