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Advanced model structures applied to system identification of a servohydraulic test rig

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Języki publikacji
EN
Abstrakty
EN
Purpose: This paper deals with a method for the parametric system identification of a nonlinear system to obtain its parametric representation using a linear transfer function. Such representation is applicable in off-line profile correction methods minimizing the error between a reference input signal and a signal performed by the test rig. In turn, a test signal can be perfectly tracked by a servo-hydraulic test rig. This is the requirement in massive production where short test sequences are repeated to validate the products. Design/methodology/approach: A numerical and experimental case studies are presented in the paper. The numerical study presents a system identification process of a nonlinear system consisting of a linear transfer function and a nonlinear output component, being a static function. The experimental study presents a system identification process of a nonlinear system which is a servo-hydraulic test rig. The simulation data has been used to illustrate the feasibility study of the proposed approach, while the experimental data have been used to validate advanced model structures under operational conditions. Findings: The advanced model structures confirmed their better performance by means of the model fit in the time domain. Research limitations/implications: The method applies to analysis of such mechanical and hydraulic systems for which measurements are corrupted by residual harmonic disturbances resulting from system nonlinearities. Practical implications: The advanced model structures are intended to be used as inverse models in off-line signal profile correction. Originality/value: The results state the foundation for the off-line parametric error cancellation method which aims in improving tracking of load signals on servo-hydraulic test rigs.
Rocznik
Strony
96--103
Opis fizyczny
Bibliogr. 20 poz., rys., tabl.
Twórcy
autor
autor
  • Control and Measuring Systems Department, Tenneco Automotive Eastern Europe, Eastern European Engineering Center (EEEC), ul. Bojkowska 59 B, 44-100 Gliwice, Poland, piotr.czop@tenneco.com
Bibliografia
  • [1] G. E. P. Box, G. M. Jenkins, G. C. Reisnel, Time Series Analysis: Forecasting and Control, Third edition, Prentice Hall, 1994.
  • [2] T. A. Johansen, R. Murray-Smith, Multiple model approaches to modeling and control, Taylor and Francis, 1996.
  • [3] MATHWORKS Inc., Matlab System Identification Toolbox Guide, Natick, MA: The Mathowrks Inc, 2007.
  • [4] J. Moscinski, Z. Ogonowski, Advanced control with MATLAB & SIMULINK, Ellis Horwood Ltd., 1995.
  • [5] T. Söderström, P. Stoica, System identification, Prentice- Hall International, Hemel Hempstead, U.K, 1988.
  • [6] KJ. Astrom, Limitations on control system performance. European Journal of Control 6/1 (2000) 2–20.
  • [7] J. De Cuyper, D. Coppens, C. Liefooghe, J. Swevers, M. Verhaegen, Advanced drive file development methods for improved service load simulation on multi axial durability test rigs, Proceedings of the International Acoustics and Vibration Asia Conference, Singapore, 1998, 339-354.
  • [8] J. De Cuyper, D. Coppens, C. Liefooghe, J. Swevers, M. Verhaegen, Design of a multivariable feedback control system to drive durability test rigs in the automotive industry, Proceedings of the 5th European Control Conference, Karslruhe, 1999.
  • [9] J. De Cuyper, J. Swevers, M. Verhaegen, P. Sas, NVN Feedback control for signal tracking on a 4 poster in the automotive industry, Proceedings of the International Seminar “Modal Analysis” ISMA 25, Leuven, Belgium, 2000, 61-68.
  • [10] C. J. Dodds, The response of vehicle components to random road surface undulations, Ph.D. thesis, Department of Mechanical Engineering, University of Glasgow, Scotland, 1972.
  • [11] C. J. Dodds, A. R. Plummer, Laboratory road simulation for full vehicle testing: A review, Proceedings of the 7th Symposium “International Automative Technology” SIAT, Pune, India, 2001 (SAE paper No. 2001-01-0047).
  • [12] H. Peng, L. Mianzo, LQ and HN preview control for a durability simulator, Proceedings of the American Control Conference, Albuquerque, 1997, I-97123A.
  • [13] R. Pintelon, J. Schoukens, System identification: A frequency domain approach, Press and Wiley, Piscataway, 2001.
  • [14] S. Skogestad, I. Postlethwaite, Multivariate feedback control: Analysis and design, Chichester, UK: Wiley, 1996.
  • [15] L. Ljung, System identification - Theory for the User, Prentice-Hall, USA, 1999.
  • [16] K. Smolders, M. Volckaert, J. Swevers, Tracking control of nonlinear lumped mechanical continuous-time systems: A model-based iterative learning approach, Mechanical Systems and Signal Processing 22 (2008) 1896-1916.
  • [17] T. Bohlin, Practical Grey-box Process Identification: Theory and Applications (Advances in Industrial Control), Springer- Verlag, London, 2006.
  • [18] J. Świder, G. Wszołek, Vibration analysis software based on a matrix hybrid graph transformation into a structure of a block diagram method, Journal of Materials Processing Technology 157-158 (2004) 256-261.
  • [19] J. Świder, P. Michalski, G. Wszołek, Physical and geometrical data acquiring system for vibration analysis software, Journal of Materials Processing Technology 164- 165 (2005) 1444-1451.
  • [20] T. Dzitkowski, A. Dymarek, Design and examining sensitivity of machine driving systems with required frequency spectrum, Journal of Achievements in Materials and Manufacturing Engineering 26/1 (2008) 49-56.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BOS2-0022-0087
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