Title
Input design for hybrid system identification for accurate estimation of submodel regions
Abstract
This paper addresses about designing of input sequence for identification of hybrid systems as PWARX model. Identification of PWARX model requires estimation of parameter vectors and estimation of discriminant surfaces of submodels in regressor space. Since we especially focus on accuracy of discriminant surface, we propose a method to determine input which generates regressor vector data nearby the discriminant surfaces by optimizing a cost function. Since the cost function requires information about discriminant surfaces, we propose a sequential identification algorithm, which updates the model and the cost function alternatively. By this method, we can obtain a high accurate model with short input sequence. Validity of the proposed method is illustrated in numerical examples.
Year
DOI
Venue
2011
10.1109/ACC.2011.5990780
American Control Conference
Keywords
Field
DocType
identification,pwarx model,accurate estimation,cost function,discriminant surfaces,hybrid system identification,input design,parameter vectors,regressor space,sequential identification,submodel regions,vectors,data model,support vector machines,model identification,estimation,support vector machine,data models,hybrid system,kernel
Kernel (linear algebra),Data modeling,Mathematical optimization,Numerical models,Computer science,Control theory,Discriminant,Support vector machine,Algorithm,Input design,Hybrid system
Conference
ISSN
ISBN
Citations 
0743-1619
978-1-4577-0080-4
1
PageRank 
References 
Authors
0.35
2
2
Name
Order
Citations
PageRank
H. Suzuki123831.31
Yamakita, M.2133.39