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2019 | OriginalPaper | Chapter

17. Probabilistic Robustness Analysis of an Actively Controlled Structure that Operates in Harsh and Uncertain Environments

Authors : Christopher J. D’Angelo, Daniel G. Cole, John C. Collinger

Published in: Structural Health Monitoring, Photogrammetry & DIC, Volume 6

Publisher: Springer International Publishing

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Abstract

This work uses probabilistic robustness techniques to show how the stability margin of an uncertain controlled structure that operates in a harsh, potentially radioactive environment can be analyzed in order to find a less conservative destabilizing uncertainty perturbation. The uncertainty is quantified in terms of a measure on the size of the covariance matrix in a multivariate Gaussian distribution. This uncertainty is used to capture the aggregate effects on a structure’s dynamic behavior due to material changes resulting from radiation embrittlement and mechanical fatigue. A probabilistic-robust full-state feedback \({\mathcal {H}_\infty }\) controller is synthesized for a low-dimensional structural model using a technique known as scenario-based probabilistic-robust synthesis. A probabilistic-robust stability margin is defined and extracted from a stability degradation function, demonstrating that a fourfold increase in the amount of uncertainty in the model can be tolerated if the designer is willing to concede a small probability that the actively-controlled structure may be unstable for certain system configurations.

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Literature
1.
go back to reference Tempo, R., Calafiore, G., Dabbene, F.: Randomized Algorithms for Analysis and Control of Uncertain Systems with Applications, 2nd ed. Springer, London (2013) Tempo, R., Calafiore, G., Dabbene, F.: Randomized Algorithms for Analysis and Control of Uncertain Systems with Applications, 2nd ed. Springer, London (2013)
2.
go back to reference Calafiore, G., Campi, M.: The scenario approach to robust control design. IEEE Trans. Autom. Control 51(5), 742–753 (2006) Calafiore, G., Campi, M.: The scenario approach to robust control design. IEEE Trans. Autom. Control 51(5), 742–753 (2006)
3.
go back to reference Zhou, K., Doyle, J.C.: Essentials of Robust Control, 1st ed. Prentice Hall, Upper Saddle River, New Jersey (1999) Zhou, K., Doyle, J.C.: Essentials of Robust Control, 1st ed. Prentice Hall, Upper Saddle River, New Jersey (1999)
4.
go back to reference Green, M., Limebeer, D.J.: Linear Robust Control, 1st ed. Dover Publications, Mineola, New York (2012) Green, M., Limebeer, D.J.: Linear Robust Control, 1st ed. Dover Publications, Mineola, New York (2012)
5.
go back to reference Young, P.M., Newlin, M.P., Doyle, J.: μ analysis with real parametric uncertainty. In: 30th Conference on Decision and Control, pp. 1251–1256 (1991) Young, P.M., Newlin, M.P., Doyle, J.: μ analysis with real parametric uncertainty. In: 30th Conference on Decision and Control, pp. 1251–1256 (1991)
6.
go back to reference Doyle, J., Packard, A., Zhou, K.: Review of LFTs, LMIs, and μ. In: Proceedings of the 30th IEEE Conference on Decision and Control, vol. 2, pp. 1227–1232 (1991) Doyle, J., Packard, A., Zhou, K.: Review of LFTs, LMIs, and μ. In: Proceedings of the 30th IEEE Conference on Decision and Control, vol. 2, pp. 1227–1232 (1991)
7.
go back to reference Doyle, J.C.: Guaranteed margins for LQG regulators. In: IEEE Trans. Autom. Control 23(4), 756–757 (1978) Doyle, J.C.: Guaranteed margins for LQG regulators. In: IEEE Trans. Autom. Control 23(4), 756–757 (1978)
8.
go back to reference Blondel, V.D., Tsitsiklis, J.N.: A survey of computational complexity results in systems and control. Automatica 36(9), 1249–1274 (2000) Blondel, V.D., Tsitsiklis, J.N.: A survey of computational complexity results in systems and control. Automatica 36(9), 1249–1274 (2000)
9.
go back to reference Ray, L.R., Stengel, R.: Application of stochastic robustness to aircraft control systems. J. Guid. Control. Dyn. 14(6), 1251–1259 (1991) Ray, L.R., Stengel, R.: Application of stochastic robustness to aircraft control systems. J. Guid. Control. Dyn. 14(6), 1251–1259 (1991)
10.
go back to reference Ray, L.R., Stengel, R.F.: A Monte Carlo approach to the analysis of control system robustness. Automatica 29(1), 229–236 (1993) Ray, L.R., Stengel, R.F.: A Monte Carlo approach to the analysis of control system robustness. Automatica 29(1), 229–236 (1993)
11.
go back to reference Marrison, C.I., Stengel, R.: Stochastic robustness synthesis applied to a benchmark control problem. Int. J. Rob. Nonlinear Control 5(1), 13–31 (1995) Marrison, C.I., Stengel, R.: Stochastic robustness synthesis applied to a benchmark control problem. Int. J. Rob. Nonlinear Control 5(1), 13–31 (1995)
12.
go back to reference Marrison, C., Stengel, R.: Design of robust control systems for a hypersonic aircraft. J. Guid. Control. Dyn. 21(1), 58–63 (1998) Marrison, C., Stengel, R.: Design of robust control systems for a hypersonic aircraft. J. Guid. Control. Dyn. 21(1), 58–63 (1998)
13.
go back to reference Marrison, C.I., Stengel, R.F.: Robust control system design using random search and genetic algorithms. English 42(6), 835–839 (1997) Marrison, C.I., Stengel, R.F.: Robust control system design using random search and genetic algorithms. English 42(6), 835–839 (1997)
14.
go back to reference Guo, S.-X.: An efficient reliability method for probabilistic h-infinity robust control of uncertain linear dynamic systems. J. Vib. Control 21(15), 2946–2958 (2014) Guo, S.-X.: An efficient reliability method for probabilistic h-infinity robust control of uncertain linear dynamic systems. J. Vib. Control 21(15), 2946–2958 (2014)
15.
go back to reference Ditlevsen, O., Madsen, H.O.: Structural Reliability Methods, 1st ed. Wiley, Chichester (2007) Ditlevsen, O., Madsen, H.O.: Structural Reliability Methods, 1st ed. Wiley, Chichester (2007)
16.
go back to reference May, B., Beck, J.L.: Probabilistic control for the active mass driver benchmark structural model. Earthq. Eng. Struct. Dyn. 27(11), 1331–1346 (1998) May, B., Beck, J.L.: Probabilistic control for the active mass driver benchmark structural model. Earthq. Eng. Struct. Dyn. 27(11), 1331–1346 (1998)
17.
go back to reference Crespo, L.G., Kenny, S.P.: Robust control design for systems with probabilistic uncertainty. Technical report NASA/TP?2005?213531, NASA (2005) Crespo, L.G., Kenny, S.P.: Robust control design for systems with probabilistic uncertainty. Technical report NASA/TP?2005?213531, NASA (2005)
18.
go back to reference Crespo, L.G., Kenny, S.P.: Reliability-based control design for uncertain systems. J. Guid. Control. Dyn. 28(4), 1–30 (2005) Crespo, L.G., Kenny, S.P.: Reliability-based control design for uncertain systems. J. Guid. Control. Dyn. 28(4), 1–30 (2005)
19.
go back to reference Soize, C.: A comprehensive overview of a non-parametric probabilistic approach of model uncertainties for predictive models in structural dynamics. Sound Vib. 288(3), 623–652 (2005) Soize, C.: A comprehensive overview of a non-parametric probabilistic approach of model uncertainties for predictive models in structural dynamics. Sound Vib. 288(3), 623–652 (2005)
20.
go back to reference Stefanou, G.: The stochastic finite element method: past, present and future. Comput. Methods Appl. Mech. Eng. 198(9–12), 1031–1051 (2009) Stefanou, G.: The stochastic finite element method: past, present and future. Comput. Methods Appl. Mech. Eng. 198(9–12), 1031–1051 (2009)
21.
go back to reference Schuëller, G.I.: Computational stochastic mechanics – recent advances. Comput. Struct. 79(22–25), 2225–2234 (2001) Schuëller, G.I.: Computational stochastic mechanics – recent advances. Comput. Struct. 79(22–25), 2225–2234 (2001)
22.
go back to reference Gahinet, P., Apkarian, P.: A linear matrix inequality approach to \(\mathcal {h}_\infty \) control. Int. J. Rob. Nonlinear Control 4(4), 421–448 (1994) Gahinet, P., Apkarian, P.: A linear matrix inequality approach to \(\mathcal {h}_\infty \) control. Int. J. Rob. Nonlinear Control 4(4), 421–448 (1994)
23.
go back to reference Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V.: Linear Matrix Inequalities in System and Control Theory, vol. 15. SIAM, Philadelphia, Pennsylvania (1994) Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V.: Linear Matrix Inequalities in System and Control Theory, vol. 15. SIAM, Philadelphia, Pennsylvania (1994)
24.
go back to reference Grant, M.C., Boyd, S.P.: The CVX Users’ Guide. Technical report release 2.1, CVX research (2015) Grant, M.C., Boyd, S.P.: The CVX Users’ Guide. Technical report release 2.1, CVX research (2015)
Metadata
Title
Probabilistic Robustness Analysis of an Actively Controlled Structure that Operates in Harsh and Uncertain Environments
Authors
Christopher J. D’Angelo
Daniel G. Cole
John C. Collinger
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-319-74476-6_17

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