A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Artificial Intelligence
Artificial Intelligence
A correction to the algorithm in Reiter's theory of diagnosis
Artificial Intelligence
Readings in model-based diagnosis
Readings in model-based diagnosis
Automated modelling of physical systems
Automated modelling of physical systems
Formal Methods in System Design - Special issue on The First Federated Logic Conference (FLOC'96), part II
A comparison of structural CSP decomposition methods
Artificial Intelligence
Automatic Symbolic Verification of Embedded Systems
IEEE Transactions on Software Engineering
Mode Estimation of Probabilistic Hybrid Systems
HSCC '02 Proceedings of the 5th International Workshop on Hybrid Systems: Computation and Control
Hybrid Estimation of Complex Systems (Lecture Notes in Control and Information Sciences)
Hybrid Estimation of Complex Systems (Lecture Notes in Control and Information Sciences)
Hybrid estimation of complex systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Improving Robustness of Mobile Robots Using Model-based Reasoning
Journal of Intelligent and Robotic Systems
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Modern artifacts are typically composed of many system components and exhibit a complex pattern of continuous/discrete behaviors. A concurrent hybrid automaton is a powerful modeling concept to capture such a system's behavior in terms a concurrent composition of hybrid automata for the individual system components. Because of the potentially large number of modes of the concurrent automaton model it is non-trivial to validate the composition such that every possible operational mode leads to a causally valid dynamic model for the overall system. This paper presents a novel model analysis method that validates the automata composition without the necessity to analyze a prohibitively large number of modes. We achieve this by formulating the exhaustive causal analysis of hybrid automata as a diagnosis problem. This provides causal specifications of the component automata and enables us to efficiently calculate the causal relationships for their concurrent composition and thus validate a concurrent automaton model.