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
Link To Document