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September  2017, 7(3): 251-271. doi: 10.3934/naco.2017017

Adaptive Neuro-Fuzzy vibration control of a smart plate

School of Production Engineering and Management, Technical University of Crete, GR-73100, Chania, Greece

* Corresponding author: gestavr@dpem.tuc.gr

Received  November 2016 Revised  June 2017 Published  July 2017

In the present paper, the vibration supression of a smart plate with the use of ANFIS (Adaptive Neuro-Fuzzy Inference System) is investigated. The whole system consists of a nonlinear mechanical model, which is an extension of the von Kármán plate model with control. The structure is subjected to external disturbances and generalized control forces. Initial and boundary conditions are set up. The initial boundary value problem is spatially-discretized by a time spectral method. The obtained discretized model is a system of nonlinear ordinary differential equations (ODEs) with respect to time. A neuro-fuzzy inference system is built and tested in order to create a nonlinear controller for the vibration supression of the plate. More specifically, a Sugeno-type fuzzy inference system is employed and trained through ANFIS. The inputs of the controller are the displacement and the velocity and the output is the control force. An effective optimization procedure is proposed and numerical results are presented.

Citation: Aliki D. Muradova, Georgios K. Tairidis, Georgios E. Stavroulakis. Adaptive Neuro-Fuzzy vibration control of a smart plate. Numerical Algebra, Control & Optimization, 2017, 7 (3) : 251-271. doi: 10.3934/naco.2017017
References:
[1]

Ph. G. Ciarlet, Mathematical Elasticity, Ⅴ. Ⅱ: Theory of Plates, Elsevier, Amsterdam, 1997.  Google Scholar

[2]

P. Ciarlet and P. Rabier, Les Equations de von Kármán, Springer-Verlag, Berlin, Heidelberg, New York, 1980.  Google Scholar

[3]

Ph. Destuynder and M. Salaun, Mathematical Analysis of Thin Plate Models, Mathématiques & Applications (Berlin) [Mathematics & Applications], Springer, 1996. doi: 10.1007/978-3-642-51761-7.  Google Scholar

[4]

D. Driankov, H. Hellendoorn and M. Reinfrank, An Introduction to Fuzzy Control, 2nd edition, Springer-Verlag, Berlin, Heidelberg, New York, 1996. Google Scholar

[5]

G. Duvaut and J. L. Lions, Les Inequations en Mecaniques et en Physiques, Dunod, 1972.  Google Scholar

[6]

N. R. Fisco and H. Adeli, Smart structures: Part Ⅱ: Hybrid control systems and control strategies, Scientia Iranica, 18 (2011), 285-295.   Google Scholar

[7]

A. Isidori, Nonlinear Control Systems, 3rd edition, Springer Verlag, London, 1995. doi: 10.1007/978-1-84628-615-5.  Google Scholar

[8]

S. Korkmaz, A review of active structural control: challenges for engineering informatics, Comput. and Struct., 89 (2011), 2113-2132.   Google Scholar

[9]

P. KoutsianitisG. K. TairidisG. A. DrosopoulosG. A. Foutsitzi and G. E. Stavroulakis, Effectiveness of optimized fuzzy controllers on partially delaminated piezocomposites, Acta Mechanica, 228 (2017), 1373-1392.  doi: 10.1007/s00707-016-1771-6.  Google Scholar

[10]

A. D. Muradova, A time spectral method for solving the nonlinear dynamic equations of a rectangular elastic plate, J. Eng. Math., 92 (2015), 83-101.  doi: 10.1007/s10665-014-9752-z.  Google Scholar

[11]

A. D. Muradova and G. E. Stavroulakis, Fuzzy vibration control of a smart plate, Int. J. Comput. Meth. Eng. Sci. Mech., 14 (2013), 212-220.  doi: 10.1080/15502287.2012.711427.  Google Scholar

[12]

A. D. Muradova and G. E. Stavroulakis, Hybrid control of vibrations of smart von Kármán, Acta Mechanica, 226 (2015), 3463-3475.  doi: 10.1007/s00707-015-1387-2.  Google Scholar

[13]

R. E. Precup and H. Hellendoorn, A survey on industrial applications of fuzzy control, Computers in Industry, 62 (2011), 213-226.   Google Scholar

[14]

A. Preumont, Vibration Control of Active Structures, Springer, 2002. doi: 10.1007/978-94-007-2033-6.  Google Scholar

[15]

J. N. Reddy, Theory and Analysis of Elastic Plates and Shells, CRC Press, Taylor & Francis, 2007. Google Scholar

[16]

A. H. N. ShiraziH. R. Owji and M. Rafeeyan, Active vibration control of an FGM rectangular plate using fuzzy logic controllers, Procedia Engineering, 14 (2011), 3019-3026.   Google Scholar

[17]

G. K. Tairidis, G. E. Stavroulakis, D. G. Marinova and E. C. Zacharenakis, Classical and soft robust active control of smart beams, Computat. Struct. Dynamics and Earthquake Engineer. (eds. Papadrakis, M. , Charmpis, D. C. Lagaros and N. D. , Tsompanakis), CRC Press/Balkema and Taylor & Francis Group, London, UK. , Ch. 11 (2009), 165–178. Google Scholar

[18]

A. R. TavakolpourM. MailahI. Z. M. Darus and O. Tokhi, Self-learning active vibration control of a flexible plate structure with piezoelectric actuator, Simul. Model. Prac. and Theory, 18 (2010), 516-532.   Google Scholar

[19]

Q. WenzhongaS. Jincaib and Q. Yangc, Active control of vibration using a fuzzy control method, J. of Sound and Vibration, 275 (2004), 917-930.  doi: 10.1016/S0022-460X(03)00795-8.  Google Scholar

[20]

I. J. Zeinoun and F. Khorrami, An adaptive control scheme based on fuzzy logic and its application to smart structures, Smart Mater. Struct., 3 (1994), 266-276.   Google Scholar

show all references

References:
[1]

Ph. G. Ciarlet, Mathematical Elasticity, Ⅴ. Ⅱ: Theory of Plates, Elsevier, Amsterdam, 1997.  Google Scholar

[2]

P. Ciarlet and P. Rabier, Les Equations de von Kármán, Springer-Verlag, Berlin, Heidelberg, New York, 1980.  Google Scholar

[3]

Ph. Destuynder and M. Salaun, Mathematical Analysis of Thin Plate Models, Mathématiques & Applications (Berlin) [Mathematics & Applications], Springer, 1996. doi: 10.1007/978-3-642-51761-7.  Google Scholar

[4]

D. Driankov, H. Hellendoorn and M. Reinfrank, An Introduction to Fuzzy Control, 2nd edition, Springer-Verlag, Berlin, Heidelberg, New York, 1996. Google Scholar

[5]

G. Duvaut and J. L. Lions, Les Inequations en Mecaniques et en Physiques, Dunod, 1972.  Google Scholar

[6]

N. R. Fisco and H. Adeli, Smart structures: Part Ⅱ: Hybrid control systems and control strategies, Scientia Iranica, 18 (2011), 285-295.   Google Scholar

[7]

A. Isidori, Nonlinear Control Systems, 3rd edition, Springer Verlag, London, 1995. doi: 10.1007/978-1-84628-615-5.  Google Scholar

[8]

S. Korkmaz, A review of active structural control: challenges for engineering informatics, Comput. and Struct., 89 (2011), 2113-2132.   Google Scholar

[9]

P. KoutsianitisG. K. TairidisG. A. DrosopoulosG. A. Foutsitzi and G. E. Stavroulakis, Effectiveness of optimized fuzzy controllers on partially delaminated piezocomposites, Acta Mechanica, 228 (2017), 1373-1392.  doi: 10.1007/s00707-016-1771-6.  Google Scholar

[10]

A. D. Muradova, A time spectral method for solving the nonlinear dynamic equations of a rectangular elastic plate, J. Eng. Math., 92 (2015), 83-101.  doi: 10.1007/s10665-014-9752-z.  Google Scholar

[11]

A. D. Muradova and G. E. Stavroulakis, Fuzzy vibration control of a smart plate, Int. J. Comput. Meth. Eng. Sci. Mech., 14 (2013), 212-220.  doi: 10.1080/15502287.2012.711427.  Google Scholar

[12]

A. D. Muradova and G. E. Stavroulakis, Hybrid control of vibrations of smart von Kármán, Acta Mechanica, 226 (2015), 3463-3475.  doi: 10.1007/s00707-015-1387-2.  Google Scholar

[13]

R. E. Precup and H. Hellendoorn, A survey on industrial applications of fuzzy control, Computers in Industry, 62 (2011), 213-226.   Google Scholar

[14]

A. Preumont, Vibration Control of Active Structures, Springer, 2002. doi: 10.1007/978-94-007-2033-6.  Google Scholar

[15]

J. N. Reddy, Theory and Analysis of Elastic Plates and Shells, CRC Press, Taylor & Francis, 2007. Google Scholar

[16]

A. H. N. ShiraziH. R. Owji and M. Rafeeyan, Active vibration control of an FGM rectangular plate using fuzzy logic controllers, Procedia Engineering, 14 (2011), 3019-3026.   Google Scholar

[17]

G. K. Tairidis, G. E. Stavroulakis, D. G. Marinova and E. C. Zacharenakis, Classical and soft robust active control of smart beams, Computat. Struct. Dynamics and Earthquake Engineer. (eds. Papadrakis, M. , Charmpis, D. C. Lagaros and N. D. , Tsompanakis), CRC Press/Balkema and Taylor & Francis Group, London, UK. , Ch. 11 (2009), 165–178. Google Scholar

[18]

A. R. TavakolpourM. MailahI. Z. M. Darus and O. Tokhi, Self-learning active vibration control of a flexible plate structure with piezoelectric actuator, Simul. Model. Prac. and Theory, 18 (2010), 516-532.   Google Scholar

[19]

Q. WenzhongaS. Jincaib and Q. Yangc, Active control of vibration using a fuzzy control method, J. of Sound and Vibration, 275 (2004), 917-930.  doi: 10.1016/S0022-460X(03)00795-8.  Google Scholar

[20]

I. J. Zeinoun and F. Khorrami, An adaptive control scheme based on fuzzy logic and its application to smart structures, Smart Mater. Struct., 3 (1994), 266-276.   Google Scholar

Figure 1.  The structure of a fuzzy inference system
Figure 2.  Displacement (input 1) membership functions
Figure 3.  Velocity (input 2) membership functions
Figure 4.  Control force (output) membership functions
Figure 5.  Displacement before and after control with Mamdani FIS ($\omega=10\pi$)
Figure 6.  Velocity before and after control with Mamdani FIS ($\omega=10\pi$)
Figure 7.  External and Control forces with Mamdani FIS ($\omega=10\pi$)
Figure 8.  Clusters of input 1 (Displacement)
Figure 9.  Clusters of input 2 (Velocity)
Figure 10.  Displacement before and after control with Sugeno FIS ($\omega=10\pi$)
Figure 11.  Velocity before and after control with Sugeno FIS ($\omega=10\pi$)
Figure 12.  External and Control forces with Sugeno FIS ($\omega=10\pi$)
Figure 13.  Displacement before and after control with Sugeno FIS ($\omega=5\pi$)
Figure 14.  Velocity before and after control with Sugenoi FIS ($\omega=5\pi$)
Figure 15.  External and Control forces with Sugenoi FIS ($\omega=5\pi$)
Figure 16.  Displacement before and after ANFIS with $\omega=10$, $D=10$ (the linear problem)
Figure 20.  Displacement before and after ANFIS with $\omega=10$, $D=50$ (the linear problem)
Figure 17.  Displacement before and after using LQR with $\omega=10$, $D=10$
Figure 21.  Displacement before and after using LQR with $\omega=10$, $D=50$
Figure 18.  Loading and control forces with ANFIS with $\omega=10$, $D=10$ (the linear problem)
Figure 22.  Loading and control forces with ANFIS with $\omega=10$, $D=50$ (the linear problem)
Figure 19.  Loading and control forces with using LQR with $\omega=10$, $D=10$
Figure 23.  Loading and control forces with using LQR with $\omega=10$, $D=50$
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