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Year 2012, Volume: 25 Issue: 2, 435 - 446, 17.04.2012

Abstract

References

  • Plummer, A. R. “Control Techniques for Structural Testing: a Review,” Proc. IMechE, J. Systems and Control Engineering, .221( I): 139- 169 (2007).
  • Tuncelli, A.C. Güner, H., Longchamp, R., “ Hydraulic Axis Control Using Pressure Feedback”, Proceeding of IEEE Int. Workshop on Intelligent Motion Control, 20-22 August,663-668 (1990).
  • Nguyen, Q.H., Ha, Q.P., Rye, D.C., Durrant- Whyte, H.F., “Force/Position Tracking for Electrohydraulic system of a Robotic Excavator,” Proceedings of 39th IEEE Conference on Desicion and Control, Australia, 5224-5229, (2000).
  • A.O. Gizatullin, K. A. Edge, “Adaptive Control for a Multi-axis Hydraulic Test Rig,,” Proc. IMechE, J. Systems and Control Engineering, 221 (I):183-198 (2006).
  • Clarke, D.W. Hinton, C. J. “Adaptive Control of Material-testing Machines,” Automatica, 33(6):1119-1131 (1997).
  • Stoten, D.P., Gόmez, E.G., “Adaptive Control of shaking tables using the minimal synthesis algorithm”, Phil. Trans. R. Soc. Lond. A, 359:1697-1723 (2001).
  • Daley, S., “Application of a fast self-tuning control algorithm to a hydraulic test rig,” Proc. IMechE, .201(C4):285-295 (1987).
  • Widrow, B., Plett, G., “Adaptive inverse control based on linear and nonlinear adaptive filtering,” in Proc. 1996 International Workshop on Neural Networks for Identification, Control, Robotics and Signal/Image Processing, Venice, Italy, 30– 38(1996).
  • Cunha, M.A.B., Guenther, R., De Pieri, E.R., “A fixed cascade controller with an adaptive dead- zone compensation scheme applied to a hydraulic actuator”, Control 2004, Bath, United Kingdom, (2004).
  • Zhidong Y., Qitao, H., Junwei, H., Hongren, L., “Adaptive Inverse Control of Random Vibration Based on The Filtered-X LMS Algorithm,” Earthquake Engineering and Engineering Vibration, 9(1):141-146, (2010).
  • De Cuyper, J. , Swevers, J., Verhaegen, M., Sas, P., “H∞ Feedback Control for Signal Tracking on a 4 Poster Test Rig in the Automotive Industry,” proceedings of the ISMA 25: 61-68 (2000).
  • De Cuyper, J., Verhaegenb, M., Swevers , J. “Off- line Feed-forward and H∞ Feedback Control on a Vibration Rig,” Control Engineering Practice, 11:129–140 (2003).
  • Vaes, D., Engelen, K., Anthonis, J., Swevers, J., Sas, P.,”Multivariable feedback Design to Improve Tracking Performance on Tractor Vibration Test Rig,” Mechanical Systems and Signal Processing, 211051-1075(2007).
  • Wijnheijmer, F. P. “Modelling and Control of a Hydraulic Servo System H∞ Control and LPV Control versus Classical Control,” Master Thesis, University of Technology Eindhoven, (2005).
  • Smolders, K., Volckaert, M., Swevers, J., “Tracking Control of Nonlinear Lumped Mechanical Continuous-time Systems: A Model Based Iterative Learning Approach,” Mechanical Systems and Signal Processing, 22.1896-1916, (2008).
  • De Cuyper, J., Vaes, D., Dehandschutter, W., Swever, J., “ Experimental H∞ Control to Improve an Industrial off-line Tracking Control Scheme on an Automotive Suspension Test Rig,” Proceeding of IEEE International Symposium on Computer Aided Control System Design, U.K, 63-68 (2002).
  • Daley, S., Hatönen , J., Owens, D.H., “Hydraulic Servo System Command Shaping Using Iterative Learning Control,” UKACC Conference, Control Bath, UK, (2004).
  • De Cuyper, J., “Linear Feedback Control for Durability Test Rigs in the Automotive Industry,” Ph. D. Thesis, Katholieke Universiteit Leuven, Belgium, (2006).
  • Cherng, J.G., Göktan, A., French, M. Gu Y.,.Jacob A., “Improving Drive Files for Vehicle Road Simulations,” Mechanical Systems and Signal Processing,15-1007-1022 (2001).
  • De Cuyper, J., Coppens, D., Liefooghe, C., Swever, J., Verhaegen, M., “ Experimental H∞ Control to Improve an Industrial off-line Tracking Control Scheme on an Automotive Suspension Test Rig,” Proceedings of IEEE International Symposium on Computer Aided Control System Design, U.K,.63-68, (2002).
  • Balkan, T., Konukseven, E. İ., Çalışkan, H., Dursun, U.,” A Control System for Vehicle Durability Test Rig,” Proceeding of the Automotive Tecnologies Congress 2010, Bursa, 2010.
  • De Cuyper, J., Coppens, D., Liefooghe, C.,. Swevers, J., Verhaegen, M., “Advanced Drive File Development Methods for Improved Service Load Simulation on Multi Axial Durability Test Rigs,” Proc. of the International Acoustics and Vibration Asia Conference, Singapore, 339-354, (1998).
  • Ercan, Y. “Akışkan Gücü Kontrolü Teorisi”, Gazi Üniversitesi Yayınları, (1995).
  • Çalışkan, H., “Modelling and Experimental Evaluation of Variable Speed Pump and Valve Controlled Hydraulic Servo Drives,” Master Thesis, Middle East Technical University, (2009).
  • Datasheet of MOOG D661 series valves.
  • W.J. Thayer, “Transfer Functions for MOOG Servovalves,” Inc., East Aurora, New York, (1958).
  • I.E. Köse , C.W. Scherer, “Robust L2-gain Feedforward Control of Uncertain Systems Using Dynamic IQCs”, Int. J. Robust and Nonlinear Control, 19:1224-1247,(2009).
  • Ljung, L. “System Identification- Theory for The User,” 2nd ed., PTR Prentice Hall, Upper Saddle River, N.J., (1999).
  • Kuo, B.C. “Automatic Control Systems,” 5th ed. , Prentice-Hall, (1987).
  • Tomizuka, M., ”Zero Phase Error Tracking
  • Algorithm for Digital Control,” J. Dynamic Systems, Measurement and Control, 109:65-68, (1987).
  • K. George, M. Verhaegen, J.M.A. Scherpen, “A systematic and Numerically Efficient Procedure for Stable Dynamic Model Inversion of LTI Systems,” In Proceedings of the 38th IEEE Conference on Decision and Control, 1881– 1886, (1999).
  • Vervoerd, M.H.A., “Iterative Learning Control- A Critical Review,” Ph. D. Thesis, University of Twente, (2005).
  • Dzielinski, A “Neural Network-based Narx
  • Models in Non-linear Adaptive Control,” In Proceedings of the Int. J. Appl. Math. Comput. Sci. , 12(2): 235–240,( 2002).
  • Vossoughi, G., Donath, M., “Dynamic feedback linearization for electrohydraulically actuated control systems,” ASME J. Dynamic Systems, Measurement and Control, 117: 469-447, (1995).
  • Q.P. Ha, Q.H. Nguyen, D.C. Rye, H.F. Durrant- Whyte, "Sliding mode control with fuzzy tuning for an electro-hydraulic position servo system," Proc. of the IEEE Int. Conf. On Knowledge- based Intelligent Electronic Systems (KES 98), Adelaide Australia, 1: 141-148, (1998).

Tracking Control Solution for Road Simulators: Model-based Iterative Learning Control Approach Improved by Time-domain Modelling

Year 2012, Volume: 25 Issue: 2, 435 - 446, 17.04.2012

Abstract

 Fatigue and durability tests are very important to develop and to optimize mechanical structure used in automotive, defence technology.  Forces in application of a product developed or being developed are named as road data. After position, force and acceleration are collected during real world application, reproducing this data of measurements in laboratory brings with a complicated control problem, as another word, it is control research area. Nonlinear structure of hydraulic actuators and test specimen with changing model parameters and noises restricts tracking performance of standard control approaches. In this paper, to reproduce the road data, “Time domain Modal-based Iterative Learning Control “procedure is recommended. The control algorithm is applied on 2-poster test rig.

References

  • Plummer, A. R. “Control Techniques for Structural Testing: a Review,” Proc. IMechE, J. Systems and Control Engineering, .221( I): 139- 169 (2007).
  • Tuncelli, A.C. Güner, H., Longchamp, R., “ Hydraulic Axis Control Using Pressure Feedback”, Proceeding of IEEE Int. Workshop on Intelligent Motion Control, 20-22 August,663-668 (1990).
  • Nguyen, Q.H., Ha, Q.P., Rye, D.C., Durrant- Whyte, H.F., “Force/Position Tracking for Electrohydraulic system of a Robotic Excavator,” Proceedings of 39th IEEE Conference on Desicion and Control, Australia, 5224-5229, (2000).
  • A.O. Gizatullin, K. A. Edge, “Adaptive Control for a Multi-axis Hydraulic Test Rig,,” Proc. IMechE, J. Systems and Control Engineering, 221 (I):183-198 (2006).
  • Clarke, D.W. Hinton, C. J. “Adaptive Control of Material-testing Machines,” Automatica, 33(6):1119-1131 (1997).
  • Stoten, D.P., Gόmez, E.G., “Adaptive Control of shaking tables using the minimal synthesis algorithm”, Phil. Trans. R. Soc. Lond. A, 359:1697-1723 (2001).
  • Daley, S., “Application of a fast self-tuning control algorithm to a hydraulic test rig,” Proc. IMechE, .201(C4):285-295 (1987).
  • Widrow, B., Plett, G., “Adaptive inverse control based on linear and nonlinear adaptive filtering,” in Proc. 1996 International Workshop on Neural Networks for Identification, Control, Robotics and Signal/Image Processing, Venice, Italy, 30– 38(1996).
  • Cunha, M.A.B., Guenther, R., De Pieri, E.R., “A fixed cascade controller with an adaptive dead- zone compensation scheme applied to a hydraulic actuator”, Control 2004, Bath, United Kingdom, (2004).
  • Zhidong Y., Qitao, H., Junwei, H., Hongren, L., “Adaptive Inverse Control of Random Vibration Based on The Filtered-X LMS Algorithm,” Earthquake Engineering and Engineering Vibration, 9(1):141-146, (2010).
  • De Cuyper, J. , Swevers, J., Verhaegen, M., Sas, P., “H∞ Feedback Control for Signal Tracking on a 4 Poster Test Rig in the Automotive Industry,” proceedings of the ISMA 25: 61-68 (2000).
  • De Cuyper, J., Verhaegenb, M., Swevers , J. “Off- line Feed-forward and H∞ Feedback Control on a Vibration Rig,” Control Engineering Practice, 11:129–140 (2003).
  • Vaes, D., Engelen, K., Anthonis, J., Swevers, J., Sas, P.,”Multivariable feedback Design to Improve Tracking Performance on Tractor Vibration Test Rig,” Mechanical Systems and Signal Processing, 211051-1075(2007).
  • Wijnheijmer, F. P. “Modelling and Control of a Hydraulic Servo System H∞ Control and LPV Control versus Classical Control,” Master Thesis, University of Technology Eindhoven, (2005).
  • Smolders, K., Volckaert, M., Swevers, J., “Tracking Control of Nonlinear Lumped Mechanical Continuous-time Systems: A Model Based Iterative Learning Approach,” Mechanical Systems and Signal Processing, 22.1896-1916, (2008).
  • De Cuyper, J., Vaes, D., Dehandschutter, W., Swever, J., “ Experimental H∞ Control to Improve an Industrial off-line Tracking Control Scheme on an Automotive Suspension Test Rig,” Proceeding of IEEE International Symposium on Computer Aided Control System Design, U.K, 63-68 (2002).
  • Daley, S., Hatönen , J., Owens, D.H., “Hydraulic Servo System Command Shaping Using Iterative Learning Control,” UKACC Conference, Control Bath, UK, (2004).
  • De Cuyper, J., “Linear Feedback Control for Durability Test Rigs in the Automotive Industry,” Ph. D. Thesis, Katholieke Universiteit Leuven, Belgium, (2006).
  • Cherng, J.G., Göktan, A., French, M. Gu Y.,.Jacob A., “Improving Drive Files for Vehicle Road Simulations,” Mechanical Systems and Signal Processing,15-1007-1022 (2001).
  • De Cuyper, J., Coppens, D., Liefooghe, C., Swever, J., Verhaegen, M., “ Experimental H∞ Control to Improve an Industrial off-line Tracking Control Scheme on an Automotive Suspension Test Rig,” Proceedings of IEEE International Symposium on Computer Aided Control System Design, U.K,.63-68, (2002).
  • Balkan, T., Konukseven, E. İ., Çalışkan, H., Dursun, U.,” A Control System for Vehicle Durability Test Rig,” Proceeding of the Automotive Tecnologies Congress 2010, Bursa, 2010.
  • De Cuyper, J., Coppens, D., Liefooghe, C.,. Swevers, J., Verhaegen, M., “Advanced Drive File Development Methods for Improved Service Load Simulation on Multi Axial Durability Test Rigs,” Proc. of the International Acoustics and Vibration Asia Conference, Singapore, 339-354, (1998).
  • Ercan, Y. “Akışkan Gücü Kontrolü Teorisi”, Gazi Üniversitesi Yayınları, (1995).
  • Çalışkan, H., “Modelling and Experimental Evaluation of Variable Speed Pump and Valve Controlled Hydraulic Servo Drives,” Master Thesis, Middle East Technical University, (2009).
  • Datasheet of MOOG D661 series valves.
  • W.J. Thayer, “Transfer Functions for MOOG Servovalves,” Inc., East Aurora, New York, (1958).
  • I.E. Köse , C.W. Scherer, “Robust L2-gain Feedforward Control of Uncertain Systems Using Dynamic IQCs”, Int. J. Robust and Nonlinear Control, 19:1224-1247,(2009).
  • Ljung, L. “System Identification- Theory for The User,” 2nd ed., PTR Prentice Hall, Upper Saddle River, N.J., (1999).
  • Kuo, B.C. “Automatic Control Systems,” 5th ed. , Prentice-Hall, (1987).
  • Tomizuka, M., ”Zero Phase Error Tracking
  • Algorithm for Digital Control,” J. Dynamic Systems, Measurement and Control, 109:65-68, (1987).
  • K. George, M. Verhaegen, J.M.A. Scherpen, “A systematic and Numerically Efficient Procedure for Stable Dynamic Model Inversion of LTI Systems,” In Proceedings of the 38th IEEE Conference on Decision and Control, 1881– 1886, (1999).
  • Vervoerd, M.H.A., “Iterative Learning Control- A Critical Review,” Ph. D. Thesis, University of Twente, (2005).
  • Dzielinski, A “Neural Network-based Narx
  • Models in Non-linear Adaptive Control,” In Proceedings of the Int. J. Appl. Math. Comput. Sci. , 12(2): 235–240,( 2002).
  • Vossoughi, G., Donath, M., “Dynamic feedback linearization for electrohydraulically actuated control systems,” ASME J. Dynamic Systems, Measurement and Control, 117: 469-447, (1995).
  • Q.P. Ha, Q.H. Nguyen, D.C. Rye, H.F. Durrant- Whyte, "Sliding mode control with fuzzy tuning for an electro-hydraulic position servo system," Proc. of the IEEE Int. Conf. On Knowledge- based Intelligent Electronic Systems (KES 98), Adelaide Australia, 1: 141-148, (1998).
There are 37 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Electrical & Electronics Engineering
Authors

Ufuk Dursun

Timuçin Bayram This is me

Publication Date April 17, 2012
Published in Issue Year 2012 Volume: 25 Issue: 2

Cite

APA Dursun, U., & Bayram, T. (2012). Tracking Control Solution for Road Simulators: Model-based Iterative Learning Control Approach Improved by Time-domain Modelling. Gazi University Journal of Science, 25(2), 435-446.
AMA Dursun U, Bayram T. Tracking Control Solution for Road Simulators: Model-based Iterative Learning Control Approach Improved by Time-domain Modelling. Gazi University Journal of Science. April 2012;25(2):435-446.
Chicago Dursun, Ufuk, and Timuçin Bayram. “Tracking Control Solution for Road Simulators: Model-Based Iterative Learning Control Approach Improved by Time-Domain Modelling”. Gazi University Journal of Science 25, no. 2 (April 2012): 435-46.
EndNote Dursun U, Bayram T (April 1, 2012) Tracking Control Solution for Road Simulators: Model-based Iterative Learning Control Approach Improved by Time-domain Modelling. Gazi University Journal of Science 25 2 435–446.
IEEE U. Dursun and T. Bayram, “Tracking Control Solution for Road Simulators: Model-based Iterative Learning Control Approach Improved by Time-domain Modelling”, Gazi University Journal of Science, vol. 25, no. 2, pp. 435–446, 2012.
ISNAD Dursun, Ufuk - Bayram, Timuçin. “Tracking Control Solution for Road Simulators: Model-Based Iterative Learning Control Approach Improved by Time-Domain Modelling”. Gazi University Journal of Science 25/2 (April 2012), 435-446.
JAMA Dursun U, Bayram T. Tracking Control Solution for Road Simulators: Model-based Iterative Learning Control Approach Improved by Time-domain Modelling. Gazi University Journal of Science. 2012;25:435–446.
MLA Dursun, Ufuk and Timuçin Bayram. “Tracking Control Solution for Road Simulators: Model-Based Iterative Learning Control Approach Improved by Time-Domain Modelling”. Gazi University Journal of Science, vol. 25, no. 2, 2012, pp. 435-46.
Vancouver Dursun U, Bayram T. Tracking Control Solution for Road Simulators: Model-based Iterative Learning Control Approach Improved by Time-domain Modelling. Gazi University Journal of Science. 2012;25(2):435-46.