Browse > Article
http://dx.doi.org/10.12989/sss.2014.14.1.017

Output-error state-space identification of vibrating structures using evolution strategies: a benchmark study  

Dertimanis, Vasilis K. (Department of Civil Engineering and Geomatics, Faculty of Engineering and Technology, Cyprus University of Technology)
Publication Information
Smart Structures and Systems / v.14, no.1, 2014 , pp. 17-37 More about this Journal
Abstract
In this study, four widely accepted and used variants of Evolution Strategies (ES) are adapted and applied to the output-error state-space identification problem. The selection of ES is justified by prior strong indication of superior performance to similar problems, over alternatives like Genetic Algorithms (GA) or Evolutionary Programming (EP). The ES variants that are being tested are (i) the (1+1)-ES, (ii) the $({\mu}/{\rho}+{\lambda})-{\sigma}$-SA-ES, (iii) the $({\mu}_I,{\lambda})-{\sigma}$-SA-ES, and (iv) the (${\mu}_w,{\lambda}$)-CMA-ES. The study is based on a six-degree-of-freedom (DOF) structural model of a shear building that is characterized by light damping (up to 5%). The envisaged analysis is taking place through Monte Carlo experiments under two different excitation types (stationary / non-stationary) and the applied ES are assessed in terms of (i) accurate modal parameters extraction, (ii) statistical consistency, (iii) performance under noise-corrupted data, and (iv) performance under non-stationary data. The results of this suggest that ES are indeed competitive alternatives in the non-linear state-space estimation problem and deserve further attention.
Keywords
structural identification; evolution strategy; optimization; state-space;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Ljung, L. (1999), System identification: theory for the user, 2nd Ed., Prentice-Hall Inc., Englewood Cliffs, NJ, USA.
2 Mc Kelvey, T. and Helmersson, A. (1997), "System identification using an over-parameterized model class - Improving the optimization algorithm", Proceedings of the 36th IEEE Conference on Decision and Control, San Diego, CA.
3 Ostermeier, A., Gawelczyk, A. and Hansen, N. (1994), "Step-size adaptation based on non-local use of selection information", in Parallel Problem Solving from Nature - PPSN III, Springer.
4 Tang, H.S., Xue S.T. and Fan. C. (2008), "Differential evolution strategy for structural system identification", Comput. Struct., 86(21-22), 2004-2012.   DOI
5 Van Overschee, P. and De Moor, B. (1996), Subspace identification for linear systems: theory - Implementation - Applications, Kluwer Academic Publishers, Dordrecht, The Netherlands.
6 Verhaegen, M. and Dewilde, P. (1992), "Subspace model identification Part 1. the output-error state-space model identification class of algorithms", Int. J. Control, 56(5), 1187-1210.   DOI   ScienceOn
7 Verhaegen, M. and Verdult, V. (2007), Filtering and system identification: a least squares approach, 2nd Ed., Prentice-Hall Inc., Englewood Cliffs, NJ, USA.
8 Viberg, M. (1995), "Subspace-based methods for the identification of linear time-invariant systems", Automatica, 31(12), 1835-1851.   DOI   ScienceOn
9 Zhang, Z., Koh, C.G. and Duan, W.H. (2010a), "Uniformly sampled genetic algorithm with gradient search for structural identification - Part I: Global search", Comput. Struct., 88(15-16), 949-962.   DOI
10 Hansen, N. (2006), The CMA evolution strategy: a comparing review, (Eds., J.A. Lozano, P. Larranga, I. Inza and E. Bengoetxea), Towards a new evolutionary computation: Advances in estimation of distribution algorithms, Springer.
11 Hansen, N. and Ostermeier, A. (2001), "Completely derandomized self-adaptation in evolution strategies", Evol. Comput., 9(2), 159-195.   DOI   ScienceOn
12 Hansen, N. and Ostermeier, A. (1997), "Convergence properties of evolution strategies with the derandomized covariance matrix adaptation: the ($\mu$/$\mu_I$,$\lambda$)-CMA-ES", Proceedings of the 5th European Congress on Intelligent techniques and Soft Computing, Aachen, Germany.
13 Koulocheris, D., Dertimanis, V.K. and Spentzas, C.N. (2008), "Parametric identification of vehicle structural characteristics", Forsch. Ingenieurwes., 68(4), 173-181.
14 Huang, C.S. (2001), "Structural identification from ambient vibration using the multivariate AR model", J. Sound Vib., 241(3), 337-359.   DOI
15 Huang, J.N. and Pappa, R.S. (1985), "An eigensystem realization algorithm (ERA) for modal parameter identification and model reduction", J. Guid. Control Dynam., 8, 620-627.   DOI   ScienceOn
16 Katayama, T. (2005), Subspace methods for system identification, Springer-Verlag, Berlin, Germany.
17 Koulocheris, D., Dertimanis, V.K. and Vrazopoulos, H. (2004), "Evolutionary parametric identification of dynamic systems", Forsch. Ingenieurwes., 72(1), 39-51.
18 Koulocheris, D., Dertimanis, V.K. and Vrazopoulos, H. (2003), "Vehicle suspension system identification using evolutionary algorithms", Proceedings of the EUROGEN 2003, Barcelona, Spain.
19 Kruisselbrink, J.W. (2012), Evolution strategies for robust optimization, PhD Thesis, Leiden University, Leiden, The Netherlands.
20 Landau, I.D. and Zito, G. (2006), Digital control systems: design, identification and implementation, Springer-Verlag, London, UK.
21 Arnold, D.V. (2006), "Weighted multirecombination evolution strategies", Theor. Comput. Sci., 361(1), 18-37.   DOI
22 Arnold, D.V. and Beyer, H.G. (2002), "Performance analysis of evolution strategies with multi-recombination in high-dimensional RN-search spaces disturbed by noise", Theor. Comput. Sci., 289(1), 629-647.   DOI
23 Casciati, S. (2008), "Stiffness identification and damage localization via differential evolution algorithms", Struct. Control Health Monit., 15(3), 436-449.   DOI   ScienceOn
24 Auger, A. (2009), "Benchmarking the (1+1) evolution strategy with one-Fifth success rule on the BBOB-2009 function testbed", Proceedings of the GECCO'09, Montreal Quebec, Canada.
25 Beyer, H.G. and Sendhoff, B. (2008), Covariance matrix adaptation revisited-the CMSA evolution strategy, (Eds., Rudolph, G., Jansen, Th., Lucas, S.M., Poloni, C. and Beume, N. ), Parallel Problem Solving from Nature - PPSN X, Springer.
26 Beyer, H.G. and Schwefel, H.P. (2002), "Evolution strategies: a comprehensive introduction", Nat. Comput., 1(1), 3-52.   DOI
27 Casciati, S. (2010), "Statistical approach to a SHM benchmark problem", Smart Struct. Syst., 6(1), 17-27.   DOI
28 Dertimanis, V.K., Koulocheris, D., Vrazopoulos, H. and Kanarachos, A. (2003), "Time-series parametric modeling using Evolution Strategy with deterministic mutation operators", Proceedings of the International Conference on Intelligent Control Systems and Signal Processing, Faro, Portugal.
29 Faravelli, L. and Casciati, S. (2004) "Structural damage detection and localization by response change diagnosis", Struct. Saf., 6(2), 104-115.
30 Fassois, S.D. (2001), "MIMO LMS-ARMAX identification of vibrating structures-Part I: the method", Mech. Syst. Signal Pr., 15(4), 737-758.   DOI
31 Franco, G., Betti, R. and Lus, H. (2004), "Identification of structural systems using an evolutionary strategy", J. Eng. Mech. -ASCE , 130(10), 1125-1139.   DOI   ScienceOn
32 Zhang, Z., Koh, C.G. and Duan, W.H. (2010b), "Uniformly sampled genetic algorithm with gradient search for structural identification - Part II: Local search", Comput. Struct., 88(19-20), 1149-1161.   DOI