TY  - CHAP
AU  - Lin, Yiqing
AU  - Fedchenia, Igor
AU  - LaBarre, Bob
AU  - Tomastik, Robert
ED  - Klingsch, Wolfram W F
ED  - Rogsch, Christian
ED  - Schadschneider, Andreas
ED  - Schreckenberg, Michael
TI  - Agent-based simulation of evacuation: An office building case study
T2  - Pedestrian and evacuation dynamics 2008
PB  - Springer Netherlands
CY  - Berlin
SN  - 3642045030
PB  - Springer Netherlands
PY  - 2010
SP  - 347
EP  - 357
PG  - 11
DO  - 10.1007/978-3-642-04504-2_30
UR  - https://m2.mtmt.hu/api/publication/24790400
ID  - 24790400
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Varigonda, S
AU  - Kalmár-Nagy, Tamás
AU  - LaBarre, B
AU  - Mezic, I
TI  - Graph decomposition methods for uncertainty propagation in complex, nonlinear interconnected dynamical systems
T2  - 2004 43rd IEEE Conference on Decision and Control (CDC)
PB  - Institute of Electrical and Electronics Engineers (IEEE)
CY  - Piscataway (NJ)
SN  - 0780386825
T3  - Proceedings of the IEEE Conference on Decision and Control, ISSN 0191-2216 ; 3.
PY  - 2004
SP  - 1794
EP  - 1798
PG  - 5
DO  - 10.1109/CDC.2004.1430306
UR  - https://m2.mtmt.hu/api/publication/2836282
ID  - 2836282
N1  - United Technologies Research Center, East Hartford, CT 06108, United States            
            Department of Mechanical Engineering, University of California, Santa Barbara, United States            
            Cited By :11            
            Export Date: 13 August 2024            
            CODEN: PCDCD            
            Correspondence Address: Varigonda, S.; United Technologies Research Center, East Hartford, CT 06108, United States
AB  - Uncertainty propagation in complex, interconnected dynamical systems can be performed more efficiently by decomposing the network based on the hierarchy and/or the strength of coupling. In this paper, we first present a structural decomposition method that identifies the hierarchy of subsystems. We briefly review the notion of horizontal-vertical decomposition (HVD) or strongly connected components (SCC) decomposition of a dynamical system and describe algorithms based on Markov chain theory and graph theory to obtain the HVD from the equation graph of the system. We also present a non-structural decomposition method to identify the weakly connected subsystems of a system based on the Laplacian of a graph derived from the Jacobian. While most of prior efforts in this direction concentrated on stability, robustness and concrete results were limited to linear systems, we use it for uncertainty propagation and study of asymptotic behavior of nonlinear interconnected systems. We illustrate the two methods using a fuel cell system example. These two methods provide a framework for efficient propagation of uncertainty in complex nonlinear systems.
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Varigonda, Subbarao
TI  - An iterative method for propagation of probability distributions in feedback systems
T2  - 2004 43rd IEEE Conference on Decision and Control (CDC)
PB  - Institute of Electrical and Electronics Engineers (IEEE)
CY  - Piscataway (NJ)
SN  - 0780386825
T3  - Proceedings of the IEEE Conference on Decision and Control, ISSN 0191-2216 ; 3.
PB  - Institute of Electrical and Electronics Engineers (IEEE)
PY  - 2004
SP  - 1803
EP  - 1805
PG  - 3
DO  - 10.1109/CDC.2004.1430308
UR  - https://m2.mtmt.hu/api/publication/24790711
ID  - 24790711
N1  - Export Date: 13 August 2024            
            CODEN: PCDCD            
            Correspondence Address: Varigonda, S.; United Technologies Research Center, East Hartford, CT 06108, United States
LA  - English
DB  - MTMT
ER  -