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 :
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