We propose a multi-objective strategy for finding effective inputs for fault detection in Cyber Physical Systems (CPSs). The main goal is to provide input signals for a system in such a way that they maximise the distance between the system’s output and an ideal target, thus leading the system towards a fault; this is based on Genetic Algorithm and Simulated Annealing heuristics. Additionally, we take into consideration the discrete locations (of hybrid system models) and a notion of input diversity to increase coverage. We implement our strategy and present an empirical analysis to estimate its effectiveness.
CITATION STYLE
Araujo, H., Carvalho, G., Mousavi, M. R., & Sampaio, A. (2019). Multi-objective Search for Effective Testing of Cyber-Physical Systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11724 LNCS, pp. 183–202). Springer Verlag. https://doi.org/10.1007/978-3-030-30446-1_10
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