Scalable static hybridization methods for analysis of nonlinear systems

S. Bak, S. Bogomolov, T.A. Henzinger, T. Johnson, P. Prakash, in:, Springer, 2016, pp. 155–164.

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Conference Paper | Published | English
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Abstract
Hybridization methods enable the analysis of hybrid automata with complex, nonlinear dynamics through a sound abstraction process. Complex dynamics are converted to simpler ones with added noise, and then analysis is done using a reachability method for the simpler dynamics. Several such recent approaches advocate that only "dynamic" hybridization techniquesi.e., those where the dynamics are abstracted on-The-fly during a reachability computation are effective. In this paper, we demonstrate this is not the case, and create static hybridization methods that are more scalable than earlier approaches. The main insight in our approach is that quick, numeric simulations can be used to guide the process, eliminating the need for an exponential number of hybridization domains. Transitions between domains are generally timetriggered, avoiding accumulated error from geometric intersections. We enhance our static technique by combining time-Triggered transitions with occasional space-Triggered transitions, and demonstrate the benefits of the combined approach in what we call mixed-Triggered hybridization. Finally, error modes are inserted to confirm that the reachable states stay within the hybridized regions. The developed techniques can scale to higher dimensions than previous static approaches, while enabling the parallelization of the main performance bottleneck for many dynamic hybridization approaches: The nonlinear optimization required for sound dynamics abstraction. We implement our method as a model transformation pass in the HYST tool, and perform reachability analysis and evaluation using an unmodified version of SpaceEx on nonlinear models with up to six dimensions.
Publishing Year
Date Published
2016-04-11
Page
155 - 164
Conference
HSCC 2016: International Conference on Hybrid Systems: Computation and Control
Conference Location
Vienna, Austria
Conference Date
2016-04-12 – 2016-04-14
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Bak S, Bogomolov S, Henzinger TA, Johnson T, Prakash P. Scalable static hybridization methods for analysis of nonlinear systems. In: Springer; 2016:155-164. doi:10.1145/2883817.2883837
Bak, S., Bogomolov, S., Henzinger, T. A., Johnson, T., & Prakash, P. (2016). Scalable static hybridization methods for analysis of nonlinear systems (pp. 155–164). Presented at the HSCC 2016: International Conference on Hybrid Systems: Computation and Control, Vienna, Austria: Springer. https://doi.org/10.1145/2883817.2883837
Bak, Stanley, Sergiy Bogomolov, Thomas A Henzinger, Taylor Johnson, and Pradyot Prakash. “Scalable Static Hybridization Methods for Analysis of Nonlinear Systems,” 155–64. Springer, 2016. https://doi.org/10.1145/2883817.2883837.
S. Bak, S. Bogomolov, T. A. Henzinger, T. Johnson, and P. Prakash, “Scalable static hybridization methods for analysis of nonlinear systems,” presented at the HSCC 2016: International Conference on Hybrid Systems: Computation and Control, Vienna, Austria, 2016, pp. 155–164.
Bak S, Bogomolov S, Henzinger TA, Johnson T, Prakash P. 2016. Scalable static hybridization methods for analysis of nonlinear systems. HSCC 2016: International Conference on Hybrid Systems: Computation and Control 155–164.
Bak, Stanley, et al. Scalable Static Hybridization Methods for Analysis of Nonlinear Systems. Springer, 2016, pp. 155–64, doi:10.1145/2883817.2883837.

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