Automatic Generation of Nonlinear Optimal Control Laws for Broom Balancing using Evolutionary Programming

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@InProceedings{chellapilla:1998:agnoclbbEP,
  author =       "Kumar Chellapilla",
  title =        "Automatic Generation of Nonlinear Optimal Control Laws
                 for Broom Balancing using Evolutionary Programming",
  booktitle =    "Proceedings of the 1998 IEEE World Congress on
                 Computational Intelligence",
  year =         "1998",
  pages =        "195--200",
  address =      "Anchorage, Alaska, USA",
  month =        "5-9 " # may,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, 3D broom
                 balancing problem, automatic nonlinear optimal control
                 law generation, bang-bang force direction, bang-bang
                 type control laws, broom balancing, evolutionary
                 computation methods, evolutionary programming, inverted
                 pendulum problem, mutation operators, state variables,
                 time optimal nonlinear control strategy, unseen input
                 states, bang-bang control, nonlinear control systems,
                 optimal control, optimisation",
  ISBN =         "0-7803-4869-9",
  file =         "c034.pdf",
  DOI =          "doi:10.1109/ICEC.1998.699500",
  size =         "6 pages",
  abstract =     "This paper explores the use of mutation operators with
                 evolutionary programming (EP) to automatically generate
                 time optimal 'bang-bang' type control laws for the
                 three dimensional broom balancing (inverted pendulum)
                 problem. EP produces a time optimal nonlinear control
                 strategy that takes the state variables as input and
                 determines the direction of the 'bang-bang' force to be
                 applied. Preliminary results indicate that the control
                 laws generated are capable of generalising over
                 previously unseen input states and compare well with
                 nonlinear control laws that were generated using other
                 evolutionary computation methods.",
  notes =        "ICEC-98 Held In Conjunction With WCCI-98 --- 1998 IEEE
                 World Congress on Computational Intelligence.
                 Comparison with \cite{koza:book} results. Also known as
                 \cite{699500}",
}

Genetic Programming entries for Kumar Chellapilla

Citations