Application of Genetic Programming for Fine Tuning PID Controller Parameters Designed Through Ziegler-Nichols Technique

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  title =        "Application of Genetic Programming for Fine Tuning
                 {PID} Controller Parameters Designed Through
                 {Ziegler-Nichols} Technique",
  author =       "Gustavo Maia {de Almeida} and 
                 Valceres Vieira Rocha {e Silva} and Erivelton Geraldo Nepomuceno and 
                 Ryuichi Yokoyama",
  year =         "2005",
  pages =        "313--322",
  editor =       "Lipo Wang and Ke Chen and Yew-Soon Ong",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "3612",
  booktitle =    "Advances in Natural Computation, First International
                 Conference, ICNC 2005, Proceedings, Part III",
  address =      "Changsha, China",
  month =        aug # " 27-29",
  bibdate =      "2005-08-01",
  bibsource =    "DBLP,
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-28320-X",
  DOI =          "doi:10.1007/11539902_37",
  size =         "10 pages",
  abstract =     "PID optimal parameters selection have been extensively
                 studied, in order to improve some strict performance
                 requirements for complex systems. Ziegler-Nichols
                 methods give estimated values for these parameters
                 based on the system's transient response. Therefore, a
                 fine tuning of these parameters is required to improve
                 the system's behaviour. In this work, genetic
                 programming is used to optimise the three parameters Kp
                 , Ti and Td , after been tuned by Ziegler-Nichols
                 method, to control a high-order process, a large time
                 delay plant and a highly non-minimum phase process. The
                 results were compared to some other tuning methods, and
                 showed to be promising.",

Genetic Programming entries for Gustavo Maia de Almeida Valceres Vieira Rocha e Silva Erivelton Geraldo Nepomuceno Ryuichi Yokoyama