A minimax control design for nonlinear systems based on genetic programming: Jung's collective unconscious approach

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{imae:2003:amcdfnsbogpjcua,
  author =       "Joe Imae and Nobuyuki Ohtsuki and 
                 Yoshiteru Kikuchi and Tomoaki Kobayashi",
  title =        "A minimax control design for nonlinear systems based
                 on genetic programming: Jung's collective unconscious
                 approach",
  booktitle =    "Proceedings of the 2003 Congress on Evolutionary
                 Computation CEC2003",
  editor =       "Ruhul Sarker and Robert Reynolds and 
                 Hussein Abbass and Kay Chen Tan and Bob McKay and Daryl Essam and 
                 Tom Gedeon",
  pages =        "1702--1707",
  year =         "2003",
  publisher =    "IEEE Press",
  address =      "Canberra",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "8-12 " # dec,
  organisation = "IEEE Neural Network Council (NNC), Engineers Australia
                 (IEAust), Evolutionary Programming Society (EPS),
                 Institution of Electrical Engineers (IEE)",
  keywords =     "genetic algorithms, genetic programming, Control
                 design, Control systems, Design methodology,
                 Differential equations, Minimax techniques, Nonlinear
                 control systems, Nonlinear systems, Optimal control,
                 Partial differential equations, minimax techniques,
                 nonlinear control systems, Jung collective unconscious,
                 difficulty-free design, minimax control problem,
                 minimax controller design, minimisation process,
                 nonlinear systems",
  ISBN =         "0-7803-7804-0",
  DOI =          "doi:10.1109/CEC.2003.1299878",
  abstract =     "When it comes to the minimax controller design, it
                 would be extremely difficult to obtain such controllers
                 in the nonlinear situations. One of the reasons is that
                 the minimax controller should be robust against any
                 kind of disturbances in the nonlinear situations. In
                 this paper, we propose a difficulty-free design method
                 of minimax control problems. First, based on the
                 genetic programming and Jung's collective unconscious,
                 this paper presents a very simple design technique to
                 solve the minimax control problems, where the minimax
                 controller may be constructed only paying attention to
                 the minimisation process. It would be surprising that
                 the maximization process is not needed in the
                 construction of minimax controllers. Then, some
                 simulations are given to demonstrate the usefulness of
                 the proposed design technique with the identification
                 problem, and minimax control problems.",
  notes =        "CEC 2003 - A joint meeting of the IEEE, the IEAust,
                 the EPS, and the IEE.",
}

Genetic Programming entries for Joe Imae Nobuyuki Ohtsuki Yoshiteru Kikuchi Tomoaki Kobayashi

Citations