DocumentCode :
3528848
Title :
Discrete abstraction for a class of stochastic hybrid systems based on bounded bisimulation
Author :
Kobayashi, Kaoru ; Fukui, Yasuhito ; Hiraishi, Kunihiko
Author_Institution :
Sch. of Inf. Sci., Japan Adv. Inst. of Sci. & Technol., Ishikawa, Japan
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
2641
Lastpage :
2646
Abstract :
Stochastic hybrid systems can express complex dynamical systems such as biological systems and communication networks, but computation for analysis and control is frequently difficult. In this paper, for a class of stochastic hybrid systems, a discrete abstraction method in which a given system is transformed into a finite-state system is proposed based on the notion of bounded bisimulation. In the existing discrete abstraction method based on bisimulation, a computational procedure is not in general terminated. In the proposed method, only the behavior for the finite time interval is expressed as a finite-state system, and termination is guaranteed. The obtained discrete abstract model can be used for model predictive control in which the finite-time optimal control problem is solved at each time. Furthermore, as an application, analysis of genetic toggle switches is also discussed.
Keywords :
linear systems; piecewise linear techniques; stochastic systems; SPWL system; biological systems; bounded bisimulation; communication networks; complex dynamical systems; discrete abstraction method; finite time interval; finite-state system; finite-time optimal control problem; genetic toggle switches analysis; model predictive control; stochastic hybrid systems; stochastic piecewise linear systems; Abstracts; Computational modeling; Genetics; Linear systems; Markov processes; Optimal control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
ISSN :
0743-1546
Print_ISBN :
978-1-4673-5714-2
Type :
conf
DOI :
10.1109/CDC.2013.6760281
Filename :
6760281
Link To Document :
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