Approximately bisimilar symbolic models for randomly switched stochastic systems |
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| Affiliation: | 1. Institute for Experimental Cancer Research in Pediatrics, Goethe-University, Komturstr. 3a, 60528 Frankfurt, Germany;2. German Cancer Consortium (DKTK), Heidelberg, Germany;3. German Cancer Research Center (DKFZ), Heidelberg, Germany;2. School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, United Kingdom;3. Dhofar University, Salalah, Oman;4. Department of Pharmaceutics, UCL School of Pharmacy, University College London, London, United Kingdom;1. Hematology, Oncology and Stem Cell Transplantation Research Center, Tehran University of Medical Sciences, Tehran, Iran;2. Blood Transfusion Research Center, High Institute for research and education in Transfusion Medicine, Tehran, Iran;1. Division of Hematology/Oncology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA;2. Division of Hematology/Oncology and Palliative Care, Department of Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA;3. Robert H. Lurie Comprehensive Cancer Center and Division of Hematology–Oncology, Department of Medicine, Northwestern University Medical School of Medicine, Chicago, IL, USA;4. Division of Hematology–Oncology, Department of Medicine, Jesse Brown Veterans Affairs Medical Center, Chicago, IL, USA;5. Division of Hematology/Oncology, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA |
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| Abstract: | In the past few years there has been a growing interest in the use of symbolic models for control systems. The main reason is the possibility to leverage algorithmic techniques over symbolic models to synthesize controllers that are valid for the concrete control systems. Such controllers can enforce complex logical specifications that are otherwise hard (if not impossible) to establish on the concrete models with classical control techniques. Examples of such specifications include those expressible via linear temporal logic or as automata on infinite strings. A relevant goal in this research line is in the identification of classes of systems that admit symbolic models: in particular, continuous-time systems with stochastic or hybrid dynamics have been only recently considered, due to their rather general and complex dynamics. In this work we make progress in this direction by enlarging the class of stochastic hybrid systems admitting finite, symbolic models: specifically, we show that randomly switched stochastic systems, satisfying some incremental stability assumption, admit such models. |
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| Keywords: | Stochastic hybrid systems Randomly switched models Symbolic models Finite abstractions Formal synthesis |
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