• DocumentCode
    1927301
  • Title

    Intelligent control of non-linear plants using type-2 fuzzy logic and neural networks

  • Author

    Melin, Patricia ; Castillo, Oscar

  • Author_Institution
    Dept. of Comput. Sci., Tijuana Technol. institute, Mexico
  • Volume
    2
  • fYear
    2003
  • fDate
    20-24 July 2003
  • Firstpage
    1558
  • Abstract
    We describe in this paper adaptive model-based control of non-linear plants using type-2 fuzzy logic and neural networks. First, the general concept of adaptive model-based control is described. Second, the use of type-2 fuzzy logic for adaptive control is described. Third, a neuro-fuzzy approach is proposed to learn the parameters of the fuzzy system for control. A specific non-linear plant is used to test the hybrid approach for adaptive control. A specific plant was used as test bed in the experiments. The non-linear plant that was considered is the "Pendubot", which is a non-linear plant similar to the two-link robot arm. The results of the type-2 fuzzy logic approach for control were good, both in accuracy and efficiency.
  • Keywords
    adaptive control; fuzzy control; fuzzy logic; fuzzy systems; intelligent control; manipulators; neurocontrollers; nonlinear control systems; Pendubot; adaptive control; fuzzy system; intelligent control; neural networks; neuro-fuzzy approach; nonlinear plants; two-link robot arm; type-2 fuzzy logic; Adaptive control; Control systems; Fuzzy control; Fuzzy logic; Fuzzy systems; Intelligent control; Neural networks; Payloads; Programmable control; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2003. Proceedings of the International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7898-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2003.1223930
  • Filename
    1223930