@inproceedings{9200,
  abstract     = {Formal design of embedded and cyber-physical systems relies on mathematical modeling. In this paper, we consider the model class of hybrid automata whose dynamics are defined by affine differential equations. Given a set of time-series data, we present an algorithmic approach to synthesize a hybrid automaton exhibiting behavior that is close to the data, up to a specified precision, and changes in synchrony with the data. A fundamental problem in our synthesis algorithm is to check membership of a time series in a hybrid automaton. Our solution integrates reachability and optimization techniques for affine dynamical systems to obtain both a sufficient and a necessary condition for membership, combined in a refinement framework. The algorithm processes one time series at a time and hence can be interrupted, provide an intermediate result, and be resumed. We report experimental results demonstrating the applicability of our synthesis approach.},
  author       = {Garcia Soto, Miriam and Henzinger, Thomas A and Schilling, Christian},
  booktitle    = {HSCC '21: Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control},
  isbn         = {9781450383394},
  keywords     = {hybrid automaton, membership, system identification},
  location     = {Nashville, TN, United States},
  pages        = {2102.12734},
  publisher    = {Association for Computing Machinery},
  title        = {{Synthesis of hybrid automata with affine dynamics from time-series data}},
  doi          = {10.1145/3447928.3456704},
  year         = {2021},
}