Fuzzy Sliding Mode Control of an MR Mount for Vibration Attenuation
In this paper, an magnetorheological (MR) mount with
fuzzy sliding mode controller (FSMC) is studied for vibration
suppression when the system is subject to base excitations. In recent
years, magnetorheological fluids are becoming a popular material in
the field of the semi-active control. However, the dynamic equation of
an MR mount is highly nonlinear and it is difficult to identify. FSMC
provides a simple method to achieve vibration attenuation of the
nonlinear system with uncertain disturbances. This method is capable
of handling the chattering problem of sliding mode control effectively
and the fuzzy control rules are obtained by using the Lyapunov
stability theory. The numerical simulations using one-dimension and
two-dimension FSMC show effectiveness of the proposed controller
for vibration suppression. Further, the well-known skyhook control
scheme and an adaptive sliding mode controller are also included in
the simulation for comparison with the proposed FSMC.
[1] Karnopp, D., Crosby, M. J., and Harwood, R. A., 1974, "Vibration
Control Using Semi-Active Force Generators," Journal of Engineering
for Industry, Vol. 96, No.2, pp. 619-626.
[2] Tseng, H. E., and Hedrick, J. K., 1994, "Semi-Active Control
LawÔÇöOptimal and Sub-Optimal," Vehicle System Dynamics, Vol. 23,
No.7, pp. 545-569.
[3] Lu, Z., 2001, "Study on Active and Semi-Active Air-Spring Suspension
Systems," Journal of the China Railway Society, Vol. 23, No. 1, pp.
33-38.
[4] Dyke, S. J., and Spencer, B. F., 1998, "Experimental Study of MR
Dampers for Seismic Protection," Smart Mat. and Stru., Vol. 7, No. 5 , pp.
693-703.
[5] Kim, B., and Roschke, P., 1999, "Linearization of Magnetorheological
Behavior Using a Neural Network," American Control Conference, Vol.
6, pp. 4501-4505.
[6] Yokoyama, M., Hedrick, J. K., and Toyama S., 2001,"A Model Following
Sliding Mode Controller for Semi-Active Suspension Systems with MR
Dampers," American Control Conference, Vol. 4, pp. 2652-2657.
[7] Shen, Y., Yang, S., and Liu, X., 2001, "Study on Improved Type of
Semi-Active Car Suspension with Magnetorheological Damper," Journal
of Vibration, Measurement & Diagnosis, Vol. 21, No. 4, pp. 253-257.
[8] Choi, S. B., Lee, H. S., and Park, Y. P., 2002, " ∞ H Control Performance
of a Full-Vehicle Suspension Featuring Magnetorheological Dampers,"
Vehicle System Dynamics, Vol. 38, No. 5, pp. 341-360.
[9] Choi, S. B., Song, H. J., Lee, H. H., Lim, S. C., Kim, J. H. ,and Choi, H. J.,
2003, "Vibration Control of a Passenger Vehicle Featuring
Magnetorheological Engine Mount," International Journal of Vehicle
Design, Vol. 33, No. 1-3, pp. 2-16.
[10] Mamdani, E. H., 1974, "Applications of Fuzzy Algorithms for Simple
Dynamics Plants," Proc. IEE, Vol. 121, No.12 , pp. 1585-1588.
[11] Chorayan, O. G., 1984, "Neurophysiological Characteristics of the Fuzzy
Logic of Problem-Solving," Cybernetics and Systems, Vol. 15, No. 3-4,
pp. 205-208.
[12] Jang, J. S. R., and Sun, C. T., 1995, "Neuro-Fuzzy Modeling and
Control," Proceedings of the IEEE, Vol. 83, No. 3, pp. 378-406.
[13] Kim, J., and Kasabov, N., 1999, "HyFIS: Adaptive Neuro-Fuzzy
Inference Systems and Their Application to Nonlinear Dynamical
Systems," Neural Networks, Vol. 12, No, 9, pp. 1301-1319.
[14] Lee, M., Lee, S. Y., and Park, C. H., 1993, "A New Neuro-Fuzzy
Identification Model of Nonlinear Dynamic Systems," International
Journal of Approximate Reasoning, Vol. 10, No. 1, pp. 29-44.
[15] Chen, C. L., and Chang, M. H., 1998, "Optimal Design of Fuzzy
Sliding-Mode Control: A Comparative Study," Fuzzy Sets and Systems,
Vol. 93, No. 1, pp. 37-48.
[16] Huang, S. J., and Lin, W. C., 2003, "Adaptive Fuzzy Controller with
Sliding Surface for Vehicle Suspension Control," IEEE Transactions on
Fuzzy Systems, Vol. 11, No. 4, pp. 550-559.
[17] Yu, F. M., Chung, H. Y., and Chen, S. Y., 2003, "Fuzzy Sliding Mode
Controller Design for Uncertain Time-Delayed Systems with Nonlinear
Input," Fuzzy Sets and Systems, Vol. 140, No. 2, pp. 359-374.
[18] Pan, R., Chang, Y.C., and Shaw, J., 2007, "Adaptive Control of an MR
Mount for Vibration Attenuation," Proceedings of the ICSV 14, 9-12,
July, Cairns, Australia.
[19] Takagi, T. and Sugeno, M., 1985, "Fuzzy Identification of Systems and Its
Application to Modeling and Control", IEEE Trans. On System, Men, and
Cybernetics, Vol. 15, No. 1, pp 116-132.
[1] Karnopp, D., Crosby, M. J., and Harwood, R. A., 1974, "Vibration
Control Using Semi-Active Force Generators," Journal of Engineering
for Industry, Vol. 96, No.2, pp. 619-626.
[2] Tseng, H. E., and Hedrick, J. K., 1994, "Semi-Active Control
LawÔÇöOptimal and Sub-Optimal," Vehicle System Dynamics, Vol. 23,
No.7, pp. 545-569.
[3] Lu, Z., 2001, "Study on Active and Semi-Active Air-Spring Suspension
Systems," Journal of the China Railway Society, Vol. 23, No. 1, pp.
33-38.
[4] Dyke, S. J., and Spencer, B. F., 1998, "Experimental Study of MR
Dampers for Seismic Protection," Smart Mat. and Stru., Vol. 7, No. 5 , pp.
693-703.
[5] Kim, B., and Roschke, P., 1999, "Linearization of Magnetorheological
Behavior Using a Neural Network," American Control Conference, Vol.
6, pp. 4501-4505.
[6] Yokoyama, M., Hedrick, J. K., and Toyama S., 2001,"A Model Following
Sliding Mode Controller for Semi-Active Suspension Systems with MR
Dampers," American Control Conference, Vol. 4, pp. 2652-2657.
[7] Shen, Y., Yang, S., and Liu, X., 2001, "Study on Improved Type of
Semi-Active Car Suspension with Magnetorheological Damper," Journal
of Vibration, Measurement & Diagnosis, Vol. 21, No. 4, pp. 253-257.
[8] Choi, S. B., Lee, H. S., and Park, Y. P., 2002, " ∞ H Control Performance
of a Full-Vehicle Suspension Featuring Magnetorheological Dampers,"
Vehicle System Dynamics, Vol. 38, No. 5, pp. 341-360.
[9] Choi, S. B., Song, H. J., Lee, H. H., Lim, S. C., Kim, J. H. ,and Choi, H. J.,
2003, "Vibration Control of a Passenger Vehicle Featuring
Magnetorheological Engine Mount," International Journal of Vehicle
Design, Vol. 33, No. 1-3, pp. 2-16.
[10] Mamdani, E. H., 1974, "Applications of Fuzzy Algorithms for Simple
Dynamics Plants," Proc. IEE, Vol. 121, No.12 , pp. 1585-1588.
[11] Chorayan, O. G., 1984, "Neurophysiological Characteristics of the Fuzzy
Logic of Problem-Solving," Cybernetics and Systems, Vol. 15, No. 3-4,
pp. 205-208.
[12] Jang, J. S. R., and Sun, C. T., 1995, "Neuro-Fuzzy Modeling and
Control," Proceedings of the IEEE, Vol. 83, No. 3, pp. 378-406.
[13] Kim, J., and Kasabov, N., 1999, "HyFIS: Adaptive Neuro-Fuzzy
Inference Systems and Their Application to Nonlinear Dynamical
Systems," Neural Networks, Vol. 12, No, 9, pp. 1301-1319.
[14] Lee, M., Lee, S. Y., and Park, C. H., 1993, "A New Neuro-Fuzzy
Identification Model of Nonlinear Dynamic Systems," International
Journal of Approximate Reasoning, Vol. 10, No. 1, pp. 29-44.
[15] Chen, C. L., and Chang, M. H., 1998, "Optimal Design of Fuzzy
Sliding-Mode Control: A Comparative Study," Fuzzy Sets and Systems,
Vol. 93, No. 1, pp. 37-48.
[16] Huang, S. J., and Lin, W. C., 2003, "Adaptive Fuzzy Controller with
Sliding Surface for Vehicle Suspension Control," IEEE Transactions on
Fuzzy Systems, Vol. 11, No. 4, pp. 550-559.
[17] Yu, F. M., Chung, H. Y., and Chen, S. Y., 2003, "Fuzzy Sliding Mode
Controller Design for Uncertain Time-Delayed Systems with Nonlinear
Input," Fuzzy Sets and Systems, Vol. 140, No. 2, pp. 359-374.
[18] Pan, R., Chang, Y.C., and Shaw, J., 2007, "Adaptive Control of an MR
Mount for Vibration Attenuation," Proceedings of the ICSV 14, 9-12,
July, Cairns, Australia.
[19] Takagi, T. and Sugeno, M., 1985, "Fuzzy Identification of Systems and Its
Application to Modeling and Control", IEEE Trans. On System, Men, and
Cybernetics, Vol. 15, No. 1, pp 116-132.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:64681", author = "Jinsiang Shaw and Ray Pan and Yin-Chieh Chang", title = "Fuzzy Sliding Mode Control of an MR Mount for Vibration Attenuation", abstract = "In this paper, an magnetorheological (MR) mount with
fuzzy sliding mode controller (FSMC) is studied for vibration
suppression when the system is subject to base excitations. In recent
years, magnetorheological fluids are becoming a popular material in
the field of the semi-active control. However, the dynamic equation of
an MR mount is highly nonlinear and it is difficult to identify. FSMC
provides a simple method to achieve vibration attenuation of the
nonlinear system with uncertain disturbances. This method is capable
of handling the chattering problem of sliding mode control effectively
and the fuzzy control rules are obtained by using the Lyapunov
stability theory. The numerical simulations using one-dimension and
two-dimension FSMC show effectiveness of the proposed controller
for vibration suppression. Further, the well-known skyhook control
scheme and an adaptive sliding mode controller are also included in
the simulation for comparison with the proposed FSMC.", keywords = "adaptive sliding mode controller, fuzzy sliding modecontroller, magnetorheological mount, skyhook control.", volume = "3", number = "12", pages = "1631-6", }
