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Validation and Verification Techniques and Tools

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Encyclopedia of Systems and Control
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Abstract

Validation and verification (V&V) of advanced control systems is required for their use in fielded systems. A comprehensive V&V process involving analysis, simulation, and experimental testing should be used to assess closed-loop system performance and identify system limitations. This entry discusses current V&V methods and tools as well as future research directions for safety-critical control applications.

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Bibliography

  • Apkarian P, Gahinet P (1995) A convex characterization of gain-scheduled Hinf controllers. IEEE Trans Autom Control AC-40(5):853–864

    Article  MathSciNet  Google Scholar 

  • Balas G, Chiang R, Packard A, Safonov M, Robust control toolboxTM, Matlab®; product family. The Mathworks Inc., Natick, MA, 1994–2014

    Google Scholar 

  • Balas G, Packard A, Seiler P, Topcu U (2013a) Robustness analysis of nonlinear systems. University of Minnesota. Website http://www.aem.umn.edu/~AerospaceControl/

  • Balas GJ, Chaing R, Packard AK, Safonov M (2013b) Robust control toolbox. The Mathworks Inc., Natick, MA

    Google Scholar 

  • Belcastro CM, Khong TH, Shin J-Y, Balas GJ, Kwatny HG, Chang B-C (2005) Uncertainty modeling for robustness analysis of control upset prevention and recovery systems. In: AIAA guidance, navigation, and control conference and exhibit, AIAA-2005-6427, San Francisco

    Chapter  Google Scholar 

  • Belcastro CM (2010) Validation and verification of future integrated safety-critical systems operating under off-nominal conditions. In: AIAA guidance, navigation and control conference, Toronto, Aug 2010

    Chapter  Google Scholar 

  • Belcastro CM (2012) Validation of safety-critical systems for aircraft loss-of-control prevention and recovery. In: AIAA guidance, navigation, and control conference, Minneapolis, Aug 2012

    Chapter  Google Scholar 

  • Berard B, Bidoit M, Finkel A, Laroussinie F, Petit A, Petrucci L, Schnoebelen P (1998) Systems and software verification: model-checking techniques and tools. Springer, Berlin

    Google Scholar 

  • Chakraborty A, Seiler P, Balas GJ (2011a) Susceptibility of F/A-18 flight controllers to the falling-leaf mode: linear analysis. J Guid Control Dyn 34(1):57–72

    Article  Google Scholar 

  • Chakraborty A, Seiler P, Balas GJ (2011b) Susceptibility of F/A-18 flight controllers to the falling-leaf mode: nonlinear analysis. J Guid Control Dyn 34(1):73–85

    Article  Google Scholar 

  • Chen C-T (1998) Linear system theory and design, 3rd edn. Oxford University Press, New York

    Google Scholar 

  • Control System ToolboxTM, Matlab®; product family. The Mathworks Inc., Natick, MA

    Google Scholar 

  • Cooper GE, Harper RP Jr (1969) The use of pilot rating in the evaluation of aircraft handling qualities. AGARD report 567, Apr 1969

    Google Scholar 

  • Doyle JC, Francis BA, Tannenbaum AR (1992) Feedback control theory, Macmillan, New York

    Google Scholar 

  • Driscol K, Madl G, Hall B (2012) Modeling and analysis of mixed synchronous/asynchronous systems. NASA/CR-2012-217756, Sept 2012

    Google Scholar 

  • Fielding C, Varga A, Bennani S, Selier M (eds) (2002) Advanced techniques for clearance of flight control laws. Springer, Berlin

    Google Scholar 

  • Foster JV, Cunningham K, Fremaux CM, Shah GH, Stewart EC, Rivers RA, Wilborn JE, Gato W (2005) Dynamics modeling and simulation of large transport airplanes in upset conditions. In: AIAA guidance, navigation, and control conference, San Francisco

    Book  Google Scholar 

  • Gill SJ, Lowenberg MH, Krauskopf B, Puyou G, Coetzee E (2012) Bifurcation analysis of the NASA GTM with a view to upset recovery. In: AIAA guidance, navigation, and control conference, Minneapolis, Aug 2012

    Chapter  Google Scholar 

  • Groen E, Ledegang W, Field J, Smaili H, Roza M, Fucke L, Nooij S, Goman M, Mayrhofer M, Zaichik L, Grigoryev M, Biryukov V (2012) SUPRA – enhanced upset recovery simulation. In: AIAA guidance, navigation, and control conference, Minneapolis, Aug 2012

    Book  Google Scholar 

  • Hartmann AK (2009) Practical guide to computer simulations. World Scientific, Hackensack, New Jersey

    Book  Google Scholar 

  • Hecker S, Varga A, Magni J (2005) Enhanced LFR toolbox for Matlab. Aerosp Sci Technol 9(2):173–180

    Article  Google Scholar 

  • Holloway CM (2012) Towards understanding the DO-178C/ED-12C assurance case. In: Proceedings of the IET 7th international conference on system safety, Edinburgh, Oct 2012

    Chapter  Google Scholar 

  • Hovakimyan N, Cao C (2010) L1 adaptive control theory. Society for Industrial and Applied Mathematics, Philadelphia

    Google Scholar 

  • IEEE (2011) IEEE guide–adoption of the Project Management Institute (PMI®;) standard a guide to the Project Management Body of Knowledge (PMBOK®; Guide), 4th edn. IEEE, p 452. doi:10.1109/IEEESTD.2011.6086685. Retrieved 7 Dec 2012

    Google Scholar 

  • Kenny SP, Crespo LG, Giesy DP (2012) UQ tools: the uncertainty quantification toolbox – introduction and tutorial. NASA TM-2012-217561, Apr 2012

    Google Scholar 

  • Khalil HK (2002) Nonlinear systems, 3rd edn. Prentice Hall, Upper Saddle River, New Jersey

    Google Scholar 

  • Kwatny HG, Dongmo J-ET, Chang B-C, Bajpai G, Yasar M, Belcastro C (2013) Nonlinear analysis of aircraft loss of control. J Guid Control Dyn 36(1):149–162

    Article  Google Scholar 

  • Kroese DP, Taimre T, Botev ZI (2011) Handbook of Monte Carlo methods. Wiley series in probability and statistics. Wiley, New York

    Book  Google Scholar 

  • Latorella KA, Feary M (2011) NASA aviation safety programs: human factors focused work. In: 16th International symposium on aviation psychology, Dayton, 2–5 May 2011

    Google Scholar 

  • Lavretsky E, Wise KA (2013) Robust and adaptive control. Springer, London

    Book  Google Scholar 

  • Liu Y, Claus RW, Litt JS, Guo T-H (2013) Simulating Effects of High Angle of Attack on Turbofan Engine Performance. In: 51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Grapevine, Texas, 7–10 January 2013

    Google Scholar 

  • Magni J-F (2004) Linear fractional representation toolbox – modeling, order reduction, and gain scheduling. ONERA technical report TR 6/08162 DSCD, Systems Control and Flight Dynamics Department, ONERA, July 2004

    Google Scholar 

  • Magni J-F (2006) User manual of the linear fractional representation toolbox (version 2.0). Technical report 5/10403.01F, ONERA/DCSD. http://www.onera.fr/staff-en/jean-marc-biannic/docs/lfrtv20s.zip

  • Matlab®;, The Mathworks Inc., Natick, MA

    Google Scholar 

  • Ogata K (1970) Modern control engineering. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Owre S, Shankar N, Rushby J (1992) PVS: a prototype verification system. In: CADE 11, Saratoga Springs, June 1992

    Google Scholar 

  • Packard AK (1994) Gain-scheduling via linear fractional transformations. Syst Control Lett 22:79–92

    Article  MathSciNet  Google Scholar 

  • Packard A, Topcu U, Seiler P, Balas G (2010) Help on SOS. IEEE Control Syst Mag 30(4):18–23

    Article  MathSciNet  Google Scholar 

  • Person SJ, Yang G, Rungta N, Khurshid S (2011) Directed incremental symbolic execution. In: 32nd ACM SIGPLAN conference on programming design and implementation, San Jose, June 4–8 2011

    Google Scholar 

  • Reif K, Gunther S, Yaz E, Unbehauen R (1999) Stochastic stability of the discrete-time extended Kalman filter. IEEE Trans Autom Control 44(4):714, 728

    Article  MathSciNet  Google Scholar 

  • Rhudy M, Gu Y, Napolitano MR (2013a) An analytical approach for comparing linearization methods in EKF and UKF. Int Journal of Adv Robot Syst, 2013, Vol. 10, 208. doi:10.5772/56370

    Google Scholar 

  • Rhudy M, Gu Y, Napolitano MR (2013b) Does the unscented Kalman filter converge faster than the extended Kalman filter? A counter example. AIAA guidance navigation and control conference, Boston, Aug 2013

    Google Scholar 

  • Rhudy M, Gu Y, Gross J, Gururajan S, Napolitano MR (2013c) Sensitivity analysis of extended and unscented Kalman filters for attitude estimation. AIAA J Aerosp Inf Syst 10(3):131–143

    Google Scholar 

  • Rugh J, Shamma J (2000) A survey of research on gain scheduling. Automatica 36:1401–1425

    Article  MathSciNet  Google Scholar 

  • Rushby J (1995) Formal methods and their role in digital systems validation for airborne systems. NASA Contractor report 4673, Aug 1995

    Google Scholar 

  • Rushby J (2009) Software verification and system assurance. In: 7th IEEE international conference on software engineering and formal methods (SEFM), Hanoi, Nov 2009

    Chapter  Google Scholar 

  • Simulink®;, The Mathworks Inc., Natick, MA

    Google Scholar 

  • Slotine J-JE, Li W (1991) Applied nonlinear control. Pearson education. Prentice Hall, Upper Saddle River, New Jersey

    Google Scholar 

  • Summers E, Chakraborty A, Tan W, Topcu U, Seiler P, Balas GJ, Packard AK (2013) Quantitative local L2-gain and reachability analysis for nonlinear systems. Int J Robust Nonlinear Control, 23:1115–1135

    Article  MathSciNet  Google Scholar 

  • Tallant GS, Hull RA, Bose P, Johnson T, Buffington JM, Krogh B, Crum VW, Prasanth R (2004) Validation & verification of intelligent and adaptive control systems. IEEEAC paper #1487, Dec 2004

    Google Scholar 

  • Varga A, Looye G, Moormann D, Grubel G (1998) Automated generation of LFT-based parametric uncertainty descriptions from generic aircraft models. Math Comput Model Dyn Syst 4:249–274

    Article  Google Scholar 

  • Varga A, Hansson A, Puyou G (2012) Optimization based clearance of flight control laws. Springer, Berlin

    Book  Google Scholar 

  • Wu F, Packard AK, Becker G (1996) Induced L2-norm control for LPV systems with bounded parameter variation rates. Int J Control 6(9/10):983–998

    MathSciNet  Google Scholar 

  • Xu X, Ulrey M, Brown JA, Mast J, Lapis MB (2013) Safety sufficiency for NextGen: assessment of selected existing safety methods, tools, processes, and regulations. NASA/CR-2013-217801, Feb 2013

    Google Scholar 

  • Zhou K, Doyle JC (1997) Essentials of robust control. Prentice Hall, Englewood Cliffs, New Jersey

    Google Scholar 

  • Zhou K, Doyle JC, Glover K (1996) Robust and optimal control. Prentice Hall, Englewood Cliffs, New Jersey

    Google Scholar 

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Belcastro, C.M. (2015). Validation and Verification Techniques and Tools. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5058-9_146

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