Simulation of Adaptronic Systems

  • Horst Baier
  • Frank Döngi


The adaptronic systems discussed in this book can be looked upon as dynamic systems with time-varying states subjected to external disturbances. To analyse and simulate such systems, basic ideas of control and system theory can be applied (see Sect. 5.2). The text concentrates on linearized, time-continuous descriptions of adaptive structures. More detailed information can be found in standard textbooks on linear (e.g. [1]) and nonlinear systems (e.g. [2]).


Design Variable Shape Memory Alloy Model Reduction Adaptive Structure Response Quantity 
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  1. 1.
    Kailath, T. (1980): Linear systems. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  2. 2.
    Slotine, J.-J.E.; Li, W. (1991): Applied nonlinear control. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  3. 3.
    Blackwood, G.H.; Ealey, M.A. (1993): Electrostrictive behavior in lead magnesium niobate (PMN) actuators. Part 1: materials perspective. Smart Materials and Structures, 2, pp. 124 - 134.CrossRefGoogle Scholar
  4. 4.
    Brinson, L.C.: One-dimensional constitutive behavior of shape memory alloys: thermomechanical derivation with non-constant material functions and redefined martensite internal-variable. J. Intelligent Material Systems and Structures, 4, pp. 229 - 242.Google Scholar
  5. 5.
    Boyd, J.G.; Lagoudas, D.C. (1994): Thermomechanical response of shape memory composites. J. Intelligent Material Systems and Structures, 5, pp. 333 - 346.CrossRefGoogle Scholar
  6. 6.
    Preumont, A.; Dufour, J.-P.; Malékian, C. (1992): Active damping by a local force feedback with piezoelectric actuators. AIAA J. Guidance, Control, and Dynamics, 15, pp. 390 - 395.CrossRefGoogle Scholar
  7. 7.
    Moore, B.C. (1981): Principal component analysis in linear systems: controllability, observability, and model reduction. IEEE Trans. Autom. Contr., AC-26, pp. 17 - 32.Google Scholar
  8. 8.
    Craig, R.R. Jr.; Su, T.-J. (1990): A review of model reduction methods for structural control design. Proc. 1st Conf. Dynamics and Control of Flexible Structures in Space, Cranfield, UK.Google Scholar
  9. 9.
    Maciejowski, J.M. (1989): Multivariable feedback design. Addison-Wesley, Wokingham, UK.Google Scholar
  10. 10.
    Biran, A.; Bremner, M. (1995): MATLAB for engineers. Addison-Wesley, Wokingham, UK.Google Scholar
  11. 11.
    Brock, D.; Lee, W.; Segalman, D.; Witkowski, W. (1994): A dynamic model of a linear actuator based on polymer hydrogel. J. Intelligent Material Systems and Structures, 5, pp. 764 - 771.CrossRefGoogle Scholar
  12. 12.
    Shahinpoor, M. (1994): Continuum electromechanics of ionic polymeric gels as artificial muscles for robotic applications. Smart Materials and Structures, 3, pp. 367 - 372.CrossRefGoogle Scholar
  13. 13.
    Shahinpoor, M. (1995): Micro-electro-mechanics of ionic polymeric gels as electrically controllable artificial muscles. J. Intelligent Material Systems and Structures, 6, pp. 307 - 314.CrossRefGoogle Scholar
  14. 14.
    Bathe, K.-J. (1982): Finite element procedures in engineering analysis. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  15. 15.
    Ha, S.K.; Keilers, C.; Chang, F.-K. (1992): Finite element analysis of composite structures containing distributed piezoelectric sensors and actuators. AIAA Journal, 30, pp. 772 - 780.CrossRefGoogle Scholar
  16. 16.
    Hwang, W.-S.; Park, H.C. (1993): Finite element modeling of piezoelectric sensors and actuators. AIAA Journal, 31, pp. 930 - 937.CrossRefGoogle Scholar
  17. 17.
    Chandrashekara, K.; Agarwal, A.N. (1993): Active vibration control of laminated composite plates using piezoelectric devices: a finite element approach. J. Intelligent Material Systems and Structures, 4, pp. 496 - 508.CrossRefGoogle Scholar
  18. 18.
    Gregory, C.Z. Jr. (1984): Reduction of large flexible spacecraft models using internal balancing theory. AIAA J. Guidance, Control, and Dynamics, 7, pp. 725732.Google Scholar
  19. 19.
    Jonckheere, E.A. (1984): Principal component analysis of flexible systems -open-loop case. IEEE Trans. Autom. Contr., AC-29, pp. 1095 - 1097.Google Scholar
  20. 20.
    Kabamba, P.T. (1985): Balanced gains and their significance for L2 model reduction. IEEE Trans. Autom. Contr., AC-30, pp. 690 - 693.Google Scholar
  21. 21.
    Al-Saggaf, U.M. (1986): On model reduction and control of discrete time systems. Ph.D. dissertation, Inform. Syst. Lab., Dept. Electr. Eng. Stanford University.Google Scholar
  22. 22.
    Lin, C.-A.; Chiu, T.-Y. (1992): Model reduction via frequency weighted balanced realization. Control Theory and Advanced Technology, 8, pp. 341 - 351.Google Scholar
  23. 23.
    Skelton, R.E.; Hughes, P.C. (1980): Modal cost analysis for linear matrixsecond-order systems. Trans. ASME, J. Dynamic Systems, Measurement, and Control, 102, pp. 151 - 158.CrossRefGoogle Scholar
  24. 24.
    Su, T.-J.; Craig, R.R. Jr. (1991): Model reduction and control of flexible structures using Krylov vectors. AIAA J. Guidance, Control, and Dynamics, 14, pp. 260 - 267.CrossRefGoogle Scholar
  25. 25.
    Czajkowsky, E.A.; Preumont, A.; Haftka, R.T. (1990): Spillover stabilization of large space structures. AIAA J. Guidance, Control, and Dynamics, 13, pp. 10001007.Google Scholar
  26. 26.
    Fehlberg, E. (1970): Klassische Runge-Kutta Formeln 4. and niedriger Ordnung mit Schrittweiten-Kontrolle and ihre Anwendung auf Wärmeleitungsprobleme. Computing, 6, pp. 61 - 71.CrossRefGoogle Scholar
  27. 27.
    Gear, C.W. (1971): Numerical initial value problems in ordinary differential equations. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  28. 28.
    ABAQUS Theory Manual Version 5.5 (1995). Hibbitt, Karlsson & Sorensen, Inc., Pawtucket, RI.Google Scholar
  29. 29.
    Gaudenzi, P.; Bathe, K.-J. (1993): Recent applications of an iterative finite element procedure for the analysis of electroelastic materials. Proc. 4th Int. Conf. on Adaptive Structures, Cologne, pp. 59 - 70.Google Scholar
  30. 30.
    Blakely, K. (1993): MSC/NASTRAN Basic Dynamic Analysis. User’s Guide, Version 68. The MacNeal-Schwendler Corp., Los Angeles, CA.Google Scholar
  31. 31.
    MATLAB product catalog (1996) The Math Works Inc., Natick, MA.Google Scholar
  32. 32.
    MATRIX= product overview (1996) Integrated Systems, Inc., Sunnyvale, CA..Google Scholar
  33. 33.
    Juang, J.-N.; Pappa, R.S. (1988): A comparative overview of modal testing and system identification for control of structures. Shock and Vibration Digest, 20, pp. 4 - 15.CrossRefGoogle Scholar
  34. 34.
    Ljung, L. (1987): System Identification — Theory for the user. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  35. 35.
    Juang, J.-N.; Pappa, R.S. (1985): An eigensystem realization algorithm for modal parameter identification and model reduction. AIAA J. Guidance, Control and Dynamics, 8, pp. 620 - 627.CrossRefGoogle Scholar
  36. 36.
    Juang, J.-N.; Phan, M.; Horta, L.G.; Longman, R.W. (1991): Identification of observer/Kalman filter Markov parameters: theory and experiment. Proc. AIAA Guidance, Control, and Navigation Conf., New Orleans, LA.Google Scholar
  37. 37.
    Juang, J.-N.; Horta, L.G.; Phan, M. (1992): User’s Guide for System/Observer/Controller Identification Toolbox. NASA Technical Memorandum 107566.Google Scholar
  38. 38.
    SPACE Products Overview (1995). dSPACE GmbH, Technologiepark 25, 33100 Paderborn, Germany.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Horst Baier
    • 1
  • Frank Döngi
    • 2
  1. 1.Lehrstuhl für LeichtbauTU MünchenGarchingGermany
  2. 2.Daimler-Benz Aerospace/Dornier Satellitensysteme GmbHFriedrichshafenGermany

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