• DocumentCode
    504710
  • Title

    Identification of hybrid system based on Probability weighted multiple ARX model

  • Author

    Taguchi, Shun ; Suzuki, Tatsuya ; Hayakawa, Soichiro ; Inagaki, Shinkichi

  • Author_Institution
    Dept. of Mech. Sci. & Eng., Nagoya Univ., Nagoya, Japan
  • fYear
    2009
  • fDate
    18-21 Aug. 2009
  • Firstpage
    4837
  • Lastpage
    4842
  • Abstract
    This paper proposes a probability weighted ARX (PrARX) model wherein the multiple ARX models are composed by the probabilistic weighting functions. As the probabilistic weighting function, a `softmax´ function is introduced. Then, the parameter estimation problem for the proposed model is formulated as a single optimization problem. Furthermore, the identified PrARX model can be easily transformed to the corresponding PWARX model with complete partitions between regions. Finally, the proposed model is applied to the modeling of the driving behavior, and the usefulness of the model is verified.
  • Keywords
    autoregressive processes; optimisation; parameter estimation; probability; transportation; PWARX model; PrARX model; autoregressive exogeneous model; driving behavior; parameter estimation problem; probabilistic weighting function; probability weighted multiple ARX model; single optimization problem; softmax function; system identification; Decision making; Electronic mail; Humans; Mathematical model; Mechanical engineering; Modeling; Motion control; Parameter estimation; Partitioning algorithms; System identification; Hybrid System; Identification; Probability-weighted ARX model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ICCAS-SICE, 2009
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-4-907764-34-0
  • Electronic_ISBN
    978-4-907764-33-3
  • Type

    conf

  • Filename
    5334385