Abstract
Safety envelopes are meant to determine under which conditions and state space regions a probabilistic property of a data-driven system can be asserted with high confidence. Dynamic data-driven applications systems (DDDAS) can make use of safety envelopes to be cognizant of the formal warranties derived from their models and assumptions. An example of safety envelopes is presented as the intersection of two simpler concepts: \(z\)-predictability and \(\tau \)-confidence; which correspond to state estimation and classification, respectively. To illustrate safety envelopes, stall detection from signal energy is shown with data gathered by piezo-electric sensors in a composite wing inside a wind tunnel under varying angles of attack and airspeed configuration. A formalization of these safety envelopes is presented in the Agda proof assistant, from which formally proven sentinel code can be generated.
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Notes
- 1.
A probabilistic statement is a statement that includes probabilistic assertions as part of its definition, e.g., the expected value after flipping a fair coin (\(0 = \text {heads}; 1 = \text {tails}\)) is \(\frac{1}{2}\).
- 2.
Full implementation and proofs can be found at http://wcl.cs.rpi.edu/pilots/fvdddas (repository name: safety-envelopes-sentinels, version 0.1.1.0).
References
Agha, G., Palmskog, K.: A survey of statistical model checking. ACM Trans. Model. Comput. Simul. 28(1), 6:1–6:39 (2018)
Ahmed, S., Amer, A., Varela, C., Kopsaftopoulos, F.: Data-driven state awareness for fly-by-feel aerial vehicles via adaptive time series and gaussian process regression models. In: Dynamic Data-Driven Applications Systems (InfoSymbiotics/DDDAS 2020) (October 2020)
Alpaydin, E.: Introduction to Machine Learning, 3rd edn. The MIT Press, Cambridge (2014)
Anand, A., Knepper, R.: ROSCoq: robots powered by constructive reals. In: Urban, C., Zhang, X. (eds.) ITP 2015. LNCS, vol. 9236, pp. 34–50. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22102-1_3
Avigad, J., Hölzl, J., Serafin, L.: A formally verified proof of the central limit theorem. J. Autom. Reason. 59(4), 389–423 (2017)
Breese, S., Kopsaftopoulos, F., Varela, C.: Towards proving runtime properties of data-driven systems using safety envelopes. In: The 12th International Workshop on Structural Health Monitoring, Stanford, CA (September 2019)
Chen, S., Imai, S., Zhu, W., Varela, C.A.: Towards learning spatio-temporal data stream relationships for failure detection in avionics. In: Blasch, E., Ravela, S., Aved, A. (eds.) Handbook of Dynamic Data Driven Applications Systems, pp. 97–121. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95504-9_5
Darema, F.: Dynamic data driven applications systems: a new paradigm for application simulations and measurements. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3038, pp. 662–669. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24688-6_86
Hasan, O., Tahar, S.: Probabilistic analysis of wireless systems using theorem proving. Electron. Notes Theor. Comput. Sci. 242(2), 43–58 (2009)
Hurd, J.: Formal verification of probabilistic algorithms. Tech. rep. UCAM-CL-TR-566, University of Cambridge, Computer Laboratory (May 2003)
Imai, S., Blasch, E., Galli, A., Zhu, W., Lee, F., Varela, C.A.: Airplane flight safety using error-tolerant data stream processing. IEEE Aerosp. Electron. Syst. Mag. 32(4), 4–17 (2017)
Kopsaftopoulos, F.: Data-driven stochastic identification for fly-by-feel aerospace structures: critical assessment of non-parametric and parametric approaches. In: AIAA Scitech 2019 Forum, p. 1534 (2019)
Kopsaftopoulos, F., Chang, F.-K.: A dynamic data-driven stochastic state-awareness framework for the next generation of bio-inspired fly-by-feel aerospace vehicles. In: Blasch, E., Ravela, S., Aved, A. (eds.) Handbook of Dynamic Data Driven Applications Systems, pp. 697–721. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95504-9_31
Kopsaftopoulos, F., Nardari, R., Li, Y.H., Chang, F.K.: Data-driven state awareness for fly-by-feel aerial vehicles: experimental assessment of a non-parametric probabilistic stall detection approach. In: Structural Health Monitoring 2017, pp. 1596–1604. DEStech Publications, Inc. (September 2017)
Luo, Z.: Computation and Reasoning: A Type Theory for Computer Science. Oxford University Press Inc., USA (1994)
Marlow, S., et al.: Haskell 2010 language report (2010). https://www.haskell.org/onlinereport/haskell2010
Norell, U.: Towards a practical programming language based on dependent type theory. Ph.D. thesis, Department of Computer Science and Engineering, Chalmers University of Technology, SE-412 96 Göteborg, Sweden (September 2007)
Paul, S., Hole, F., Zytek, A., Varela, C.A.: Flight trajectory planning for fixed wing aircraft in loss of thrust emergencies. In: Dynamic Data-Driven Application Systems (InfoSymbiotics/DDDAS 2017), Cambridge, MA (August 2017)
Pike, L., Wegmann, N., Niller, S., Goodloe, A.: Copilot: monitoring embedded systems. Innov. Syst. Softw. Eng. 9(4), 235–255 (2013)
Qasim, M., Hasan, O., Elleuch, M., Tahar, S.: Formalization of normal random variables in HOL. In: Kohlhase, M., Johansson, M., Miller, B., de de Moura, L., Tompa, F. (eds.) CICM 2016. LNCS (LNAI), vol. 9791, pp. 44–59. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-42547-4_4
Ricketts, D., Malecha, G., Alvarez, M.M., Gowda, V., Lerner, S.: Towards verification of hybrid systems in a foundational proof assistant. In: 2015 ACM/IEEE International Conference on Formal Methods and Models for Codesign (MEMOCODE), pp. 248–257 (September 2015)
Srivatanakul, T.: Security analysis with deviational techniques. Ph.D. thesis, University of York, York, UK (April 2005)
Acknowledgment
This research was partially supported by the National Science Foundation (NSF), Grant No. – CNS-1816307, and the Air Force Office of Scientific Research (AFOSR), DDDAS Grant No. – FA9550-19-1-0054.
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Cruz-Camacho, E., Paul, S., Kopsaftopoulos, F., Varela, C.A. (2020). Towards Provably Correct Probabilistic Flight Systems. In: Darema, F., Blasch, E., Ravela, S., Aved, A. (eds) Dynamic Data Driven Applications Systems. DDDAS 2020. Lecture Notes in Computer Science(), vol 12312. Springer, Cham. https://doi.org/10.1007/978-3-030-61725-7_28
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