TECHNICAL PAPERS
Jan 17, 2011

Wavelet Network for Semi-Active Control

Publication: Journal of Engineering Mechanics
Volume 137, Issue 7

Abstract

This paper proposes a wavelet neurocontroller capable of self-adaptation and self-organization for uncertain systems controlled with semiactive devices that are ideal candidates for control of large-scale civil structures. A condition on the sliding surface for cantilever-like structures is defined. The issue of applicability of the control solution to large-scale civil structures is made the central theme throughout the text, as this topic has not been extensively discussed in the literature. Stability and convergence of the proposed neurocontroller are assessed through various numerical simulations for harmonic, earthquake, and wind excitations. The simulations consist of semiactive dampers installed as a replacement for the current viscous damping system in an existing structure. The controller uses only localized measurements. Results show that the controller is stable for both active and semiactive control using limited measurements and that it is capable of outperforming passive control strategies for earthquake and wind loads. In the case of wind loads, the neurocontroller is found to also outperform a linear quadratic regulator (LQR) controller designed using full knowledge of the states and system dynamics.

Get full access to this article

View all available purchase options and get full access to this article.

References

Ahlawat, A. S., and Ramaswamy, A. (2004). “Multiobjective optimal fuzzy logic controller driven active and hybrid control systems for seismically excited nonlinear buildings.” J. Eng. Mech., 130(4), 524–530.
Avraam, M. T. (2009). “MR-fluid brake design and its application to a portable muscular rehabilitation device.” Ph.D. thesis, Université Libre de Bruxelle, Bruxelle, Belgium.
Behera, L., Kumar, S., and Patnaik, A. (2006). “On adaptive learning rate that guarantees convergence in feedforward networks.” IEEE Trans. Neural Netw., 17(5), 1116–1125.
Cannon, M., and Slotine, J. J. E. (1995). “Space-frequency localized basis function networks for nonlinear system estimation and control.” Neurocomputing, 9(3), 293–342.
Chopra, A. K. (1995). Dynamics of structures, Prentice Hall, Englewood Cliffs, NJ.
Connor, J. J. (2003). Introduction to structural motion control, Prentice Hall New York.
Dominguez, A., Sedaghati, R., and Stiharu, I. (2006). “Semi-active vibration control of adaptive structures using magnetorheological dampers.” AIAA J., 44(7), 1563–1571.
Ghaboussi, J., and Joghataie, A. (1995). “Active control of structures using neural networks.” J. Eng. Mech., 121(4), 555–567.
Grossberg, S. (1988). “Nonlinear neural networks: Principles, mechanisms, and architectures.” Neural Netw., 1(1), 17–61.
Guo, Y.-Q.,Fei, S.-M., and Xu, Z.-D. (2008). “Simulation analysis on intelligent structures with magnetorheological dampers.” J. Intell. Mater. Syst. Struct., 19(6), 715–726.
Hidaka, S., Ahn, Y. K., and Morishita, S. (1999). “Adaptive vibration control by a variable-damping dynamic absorber using ER fluid.” J. Vib. Acoust., 121(3), 373–378.
Housner, G. W., et al. (1997). “Structural control: Past, present, and future.” J. Eng. Mech., 123(9), 897–971.
Howlett, R. J., and Jain, L. C. (2001). Radial basis function networks 1: Recent developments in theory and applications, Springer Verlag, New York.
Hung, S. L., Huang, C. S., Wen, C. M., and Hsu, Y. C. (2003). “Nonparametric identification of a building structure from experimental data using wavelet neural network.” Comput. Aided Civ. Infrastruct. Eng., 18(5), 356–368.
Jansen, L. M., and Dyke, S. J. (2000). “Semiactive control strategies for MR dampers: comparative study.” J. Eng. Mech., 126(8), 795–803.
Jiménez-Fabián, R., and Alvarez-Icaza, L. (2009). “Simultaneous state estimation and parameter tuning in a shear building with a magneto-rheological damper.” Struct. Contr. Health Monit., 16(4), 483–502.
Kadirkamanathan, V., and Niranjan, M. (1993). “A function estimation approach to sequential learning with neural networks.” Neural Comput., 5(6), 954–975.
Kantz, H., and Schreiber, T. (2004). Nonlinear time series analysis, Cambridge University Press, Cambridge, UK.
Karamodin, A., and Kazemi, H., and (2010). “Semi-active control of structures using neuro-predictive algorithm for MR dampers.” Struct. Contr. Health Monit., 17(3), 237–253.
Kohonen, T. (1990). “The self-organizing map.” Proc. IEEE, 78(9), 1464–1480.
Laflamme, S., and Connor, J. J. (2009). “Application of self-tuning Gaussian networks for control of civil structures equipped with magnetorheological dampers.” Proc., Society of Photo-optical Instrumentation Engineers (SPIE), Active and Passive Smart Structures and Integrated Systems 2009, M. Ahmadian and M. Ghasemi-Nejhad, eds., Vol. 7288, SPIE, Bellingham, WA.
Laflamme, S., Yu, T.-Y., and Connor, J. J. (2009). “Intelligent controller for smart base isolation of masonry structures.” Proc., Int. Workshop on Smart Materials and Structures (CANSMART 2009), Cansmart Group, 37–46.
Lee, H. J., Yang, G., Jung, H. J., Spencer, B. F., Jr., and Lee, I. W. (2006). “Semi-active neurocontrol of a base-isolated benchmark structure.” Struct. Contr. Health Monit., 13(2–3), 682–692.
Lee, H. J., Jung, H. J., Cho, S. W., and Lee, I. W. (2008). “An experimental study of semiactive modal neuro-control scheme using MR damper for building structure.” J. Intell. Mater. Syst. Struct., 19(9), 1005–1015.
Li, H. N., and Chang, Z. G. (2008). “Semi-active control for eccentric structures with MR damper based on hybrid intelligent algorithm.” Struct. Des. Tall Special Build., 17(1), 167–180.
Lin, P. Y., and Loh, C. H. (2008). “Semi-active control of floor isolation system using MR-damper.” Proc., Society of Photo-optical Instrumentation Engineers (SPIE), Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2008, Vol. 6932, SPIE, Bellingham, WA.
Loh, C. H., and Chang, C. M. (2008). “Application of centralized and decentralized control to building structure: Analytical study.” J. Eng. Mech., 134(11), 970–982.
Lynch, J. P., Wang, Y., Swartz, R. A., Lu, K. C., and Loh, C. H. (2008). “Implementation of a closed-loop structural control system using wireless sensor networks.” Struct. Contr. Health Monit., 15(4), 518–539.
McNamara, R. J., and Taylor, D. P. (2003). “Fluid viscous dampers for high-rise buildings.” Struct. Des. Tall Special Build., 12(2), 145–154.
Morishian, S., Shiraishi, T., and Nakaya, N. (2003). “Adaptive vibration control of a structure using MR damper.” Proc., 3rd World Conf. on Structural Control, F. Casciati, ed., Wiley, Hoboken, NJ, 761–766
Narasimhan, S., and Nagarajaiah, S. (2005). “A STFT semiactive controller for base isolated buildings with variable stiffness isolation systems.” Eng. Struct., 27(4), 514–523.
Nitta, Y., Nishitani, A., and Spencer, B. F. Jr (2006). “Semiactive control strategy for smart base isolation utilizing absolute acceleration information.” Struct. Contr. Health Monit., 13(2–3), 649–659.
Nørgaard, M., Ravn, O., Poulsen, N. K., and Hansen, L. K. (2000). Neural networks for modelling and control of dynamic systems: A practitioner’s handbook, Springer Verlag, New York.
Sanner, R. M., and Slotine, J. J. E. (1992). “Gaussian networks for direct adaptive control.” IEEE Trans. Neural Netw., 3(6), 837–863.
Shook, D. A., Roschke, P. N., Lin, P. Y., and Loh, C. H. (2009). “Semi-active control of a torsionally-responsive structure.” Eng. Struct., 31(1), 57–68.
Slotine, J. J. E., and Coetsee, J. A. (1986). “Adaptive sliding controller synthesis for nonlinear systems.” Int. J. Control, 43(6), 1631–1651.
Slotine, J. J. E., and Li, W. (1991). Applied nonlinear control, Prentice Hall, Englewood Cliffs, NJ.
Song, X., Ahmadian, M., Southward, S., and Miller, L. R. (2005). “An adaptive semiactive control algorithm for magnetorheological suspension systems.” J. Vib. Acoust., 127(5), 493–502.
Soong, T. T., and Cimellaro, G. P. (2009). “Future directions in structural control.” Struct. Contr. Health Monit., 16(1), 7–16.
Spencer, B. F., Jr., and Nagarajaiah, S. (2003). “State of the art of structural control.” J. Struct. Eng., 129(7), 845–856.
Spencer, B. F., Jr., Dyke, S. J., Sain, M. K., and Carlson, J. D. (1997). “Phenomenological model for magnetorheological dampers.” J. Eng. Mech., 123(3), 230–238.
Stark, J., Broomhead, D. S., Davies, M. E., and Huke, J. (2003). “Delay embeddings for forced systems. II. Stochastic forcing.” J. Nonlinear Sci., 13(6), 519–577.
Suresh, S., Narasimhan, S., and Sundararajan, N. (2008). “Adaptive control of nonlinear smart base-isolated buildings using Gaussian kernel functions.” Struct. Contr. Health Monit., 15(4), 585–603.
Terasawa, T., Sakai, C., Ohmori, H., and Sano, A. (2004). “Adaptive identification of MR damper for vibration control.” 43rd IEEE Conf. on Decision and Control (CDC), IEEE, New York, 2297–2303.
Thai, K., Jabbari, F., and Bobrow, J. E. (1997). “Structural control via semi-active and hybrid control.” Proc., 1997American Control Conference, Vol. 1,IEEE, New York, 6–10.
Wang, S. G., Yeh, H. Y., and Roschke, P. N. (2001). “Robust control for structural systems with parametric and unstructured uncertainties.” J. Vib. Control, 7(5), 753–772.
Wongprasert, N., and Symans, M. D. (2005). “Numerical evaluation of adaptive base-isolated structures subjected to earthquake ground motions.” J. Eng. Mech., 131(2), 109–119.
Wu, J. C., Lu, W. C., and Hsu, W. C. (2006). “Implementation of a feasible control design process incorporating robustness criteria for wind-excited high-rise buildings.” J. Struct. Eng., 132(1), 89–101.
Xu, B., Wu, Z. S., and Yokoyama, K. (2003). “Neural network for decentralized control of cable-stayed bridge.” J. Bridge Eng., 8(4), 229–236.
Yang, G. (2001). “Large-scale magnetorheological fluid damper for vibration mitigation: Modeling, testing, and control.” Ph.D. thesis, Univ. of Notre Dame, Notre Dame, IN.
Yang, J. N., and Agrawal, A. K. (2002). “Semi-active hybrid control systems for nonlinear buildings against near-field earthquakes.” Eng. Struct., 24(3), 271–280.
Yang, J. N., Wu, J. C., and Agrawal, A. K. (1995). “Sliding mode control for nonlinear and hysteretic structures.” J. Eng. Mech., 121(12), 1330–1339.
Yang, G., Spencer, B. F., Jr., Carlson, J. D., and Sain, M. K. (2002). “Large-scale MR fluid dampers: modeling and dynamic performance considerations.” Eng. Struct., 24(3), 309–323.
Yoshida, O., Dyke, S. J., Giacosa, L. M., and Truman, K. Z. (2003). “Experimental verification of torsional response control of asymmetric buildings using MR dampers.” Earthquake Eng. Struct. Dyn., 32(13), 2085–2105.
Zhang, Q., Benveniste, A., and Hogskola, L. T. (1992). “Wavelet networks.” IEEE Trans. Neural Netw., 3(6), 889–898.
Zhou, L., and Wang, L. X. (2003). “Adaptive fuzzy control for nonlinear building-magnetorheological damper system.” J. Struct. Eng., 129(7), 905–913.

Information & Authors

Information

Published In

Go to Journal of Engineering Mechanics
Journal of Engineering Mechanics
Volume 137Issue 7July 2011
Pages: 462 - 474

History

Received: Dec 7, 2009
Accepted: Jan 14, 2011
Published online: Jan 17, 2011
Published in print: Jul 1, 2011

Permissions

Request permissions for this article.

Authors

Affiliations

S. Laflamme, S.M.ASCE [email protected]
Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Massachusetts Institute of Technology, Rm. #1-290, 77 Massachusetts Ave., Cambridge, MA 02139 (corresponding author). E-mail: [email protected]
J. J. E. Slotine
Professor, Mechanical Engineering and Information Sciences; and Brain and Cognitive Sciences; and Director, Nonlinear Systems Laboratory, Massachusetts Institute of Technology, Rm. #3-338, 77 Massachusetts Ave., Cambridge, MA 02139.
J. J. Connor, F.ASCE
Professor, Civil and Environmental Engineering, Massachusetts Institute of Technology, Rm. #1-253, 77 Massachusetts Ave., Cambridge, MA 02139.

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share