Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure
The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1093618Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1838
 W. M. Winslow, "Induced Fibration of Suspensions,” Journal of Applied Physics, vol. 20, 1949, pp.1137-1140.
 R. S. Stanway, J. L. Sproston, A. K. El Wahed, "Applications of electro-rheological fluids in vibration control: A survey,” Smart Mater. Struct., vol. 5, 1996, pp.464-482.
 S. B. Choi, Y. K. Park, M. S. Suh, "Elastodynamic characteristics of hollow cantilever beams containing an electro-rheological fluid: Experimental results,” AIAA J., vol. 32, 1992, pp.438-440.
 M. Yalcintas, J. Pl Coulter, D. L. Don, "Structural modeling and optimal control of electro-rheological material based adaptive beams,” Smart Mater. Struct., vol. 4, 1995, pp.207-214..
 S. B. Choi, Y. K. Park, C. C. Cheong, "Active vibration control of intelligent composite laminate structures incorporating an electro-rheological fluid,” J. Intell. Mater. Syst. Structures, vol. 7, 1996, pp.411-419.
 C. D. Rahn, S. Joshi, "Modeling and control of an electro-rheological sandwich beam,” J. Vib. Acoust., vol. 120, 1998, pp.221-227.
 K. X. Wei, G. Meng, W. M. Zhang, "Vibration characteristics of a rotating beam filled with electrorheological fluid,” J. Intell. Mater. Syst. Structures, vol. 18, 2007, pp.1165-1173.
 H. Frahm, "Device for damping vibrations of bodies,” US patent no. 989958, 1911.
 B.G. Korenev, L.M. Reznikov, "Dynamic Vibration Absorbers, Theory and Technical Applications,” Wiley, New York, 1993.
 J.P. Den Hartog, "Mechanical Vibrations,” Dover Publications Inc., 1985.
 J.B. Hunt, "Dynamic Vibration Absorbers,” Mechanical Engineering Publications Ltd., 1979.
 M. J. Brennan, "Some recent developments in adaptive tuned vibration absorbers/neutralizers,” Shock and Vibration, vol. 13, 2006, pp. 531–543.
 L. Kela, P. Vahaoja, "Recent studies of adaptive tuned vibration absorbers/neutralizers,” Applied Mechanics Reviews, vol. 62, 2009, pp. 060801-1–060801-9.
 A. K. Ghorbani-Tanha, M. Rahimian, A. Noorzad, "A novel semiactive variable stiffness device and its application in a new semiactive tuned vibration absorber,” J. Engineering Mechanics, vol. 137, 2011, pp. 390–399.
 C. Y. Lee, C. C. Chen, T. H. Yang, C. J. Lin, "Structural vibration control using a tunable hybrid shape memory material vibration absorber,” J. Intell. Mater. Syst. Structures, vol. 23, 2012, pp. 1725-1734.
 C. J. Lin, C. Y. Lee, C. H. Cheng, and G. F Chen, "Vibration Control of a Cantilever Beam Using a Tunable Vibration Absorber Embedded with ER Fluids,” International Journal of Mechanical, Industrial Science and Engineering, Vol. 7 No. 7, 2013, pp. 152-158.
 L. A. Zadeh, "The concept of a linguistic variable and its application to approximate reasoning-I,” Inf. Sci., vol. 8, 1975, pp.199-249.
 J. M. Mendel, Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions, Prentice-Hall, Upper-Saddle River, NJ, 2001.
 Z. Kovacic, M. Balenovic and S. Bogdan, "Sensitivity based self learning fuzzy logic control for a servo system,” IEEE Control Syst. Mag., vol. 18 (3), 1998, pp. 41-51.
 H. Lee, M. Tomizuka, "Robust adaptive control using a universal approximator for SISO nonlinear systems,” IEEE Trans. Fuzzy Syst., vol. 8 (1), 2000, pp. 95-106.
 J. S. Wang, C.S.G. Lee, "Self-adaptive neuro-fuzzy inference systems for classification application,” IEEE Trans. Fuzzy Syst., vol. 10 (6), 2002, pp. 790-802.
 N. Golea, A. Golea and K. Benmahammed, "Fuzzy model reference adaptive control,” IEEE Transactions on Fuzzy Systems, vol. 10 (4), 2002, pp. 436-444.
 M. Hojati, S. Gazor, "Hybrid adaptive fuzzy identification and control of nonlinear systems,” IEEE Trans. Fuzzy Syst., vol. 10 (2), 2002, pp. 198-210.
 J. M. Mendel, "Fuzzy Sets for Words: a New Beginning," Proc. IEEE FUZZ Conference, St. Louis, MO, May 26–28, 2003, pp. 37–42.
 J. M. Mendel, "Computing derivatives in interval type-2 fuzzy logic systems,” IEEE Trans. Fuzzy Syst. Vol. 12 (1), 2004, pp. 84-98.
 C. H. Wang, C. S. Cheng, C. T. Lee, "Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN).” IEEE Trans. Syst. Man Cybern. Part B, vol. 34 (3): 1462-1477. 2004.
 J. M. Mendel, "Type-2 Fuzzy Sets and Systems: an Overview,” IEEE Computational Intelligence Magazine, vol. 2, 2007, pp. 20-29.