Dependability aspects of model-based systems design for mechatronic systems
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
This paper discusses modern model-based design aspects for ensuring high dependability of mechatronic systems, i.e. ensuring most reliable and safe operation under presence of non-avoidable threats. An introductory assessment clarifies relevant terms of reference such as 'systems' (in particular mechatronic systems), 'models', 'design' and 'dependability' with special focus on the effect of threats (faults, errors, failures). The further considerations give answers to the questions 'What 'dependability' models (methods) have to be used?' and 'How to work with these 'dependability' models (methods)?' in the context of building dependable systems that are robust against threats. Results of current research at the TU Dresden Automation Engineering Lab demonstrate the successful applicability of model-based system threat analysis to control systems for robotic vehicles introducing new concepts such as dual graph error propagation model, error propagation for hybrid block diagram and finite state machine models, error propagation in multi-rate time discrete models, optimized software-implemented fault tolerance and model-based selective regression testing.
Details
| Original language | English |
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| Title of host publication | Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 15-22 |
| Number of pages | 8 |
| ISBN (electronic) | 978-1-4799-3633-5 |
| Publication status | Published - 9 Apr 2015 |
| Peer-reviewed | Yes |
Conference
| Title | 2015 IEEE International Conference on Mechatronics, ICM 2015 |
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| Duration | 6 - 8 March 2015 |
| City | Nagoya |
| Country | Japan |
External IDs
| Scopus | 84929302965 |
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Keywords
ASJC Scopus subject areas
Keywords
- automated model transform, dependability, error propagation, Markov chain, mechatronic systems, model-based design, probabilistic model