DocumentCode :
184106
Title :
Symbolic models for randomly switched stochastic systems
Author :
Zamani, Mahdi ; Abate, Alessandro
Author_Institution :
Dept. of Design Eng., Delft Univ. of Technol., Delft, Netherlands
fYear :
2014
fDate :
4-6 June 2014
Firstpage :
2291
Lastpage :
2296
Abstract :
In the past few years, there has been a growing interest in the use of symbolic models for control systems, however this has only recently covered the class of continuous-time stochastic hybrid systems. The main reason for this interest is the possibility to use algorithmic techniques over symbolic models to synthesize hybrid controllers enforcing logic specifications on the original models, which would be hard (or even impossible) to enforce with classical control techniques. Examples of such specifications include those expressible via linear temporal logic or as automata on infinite strings. The main challenge in this research line is in the identification of classes of systems that admit symbolic models. In this work we progress in this direction by enlarging the class of stochastic hybrid systems admitting such models: in particular we show that randomly switched stochastic systems, satisfying some incremental stability assumption, admit symbolic models.
Keywords :
automata theory; continuous time systems; control systems; stability; stochastic systems; temporal logic; algorithmic techniques; automata; continuous-time stochastic hybrid systems; control systems; hybrid controllers; incremental stability assumption; infinite strings; linear temporal logic; logic specifications; randomly switched stochastic systems; symbolic models; Approximation methods; Biological system modeling; Lyapunov methods; Stochastic processes; Stochastic systems; Switches; Automata; Hybrid systems; Stochastic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
ISSN :
0743-1619
Print_ISBN :
978-1-4799-3272-6
Type :
conf
DOI :
10.1109/ACC.2014.6858937
Filename :
6858937
Link To Document :
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