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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 656Adaptive Variable Universe of Discourse Fuzzy...

Adaptive Variable Universe of Discourse Fuzzy Sliding Mode Control

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Abstract:

This paper proposes adaptive variable universe of discourse fuzzy sliding mode control for efficient compensation of unbounded disturbances and reduced chattering. Classical sliding mode control is robust to bounded uncertainties and disturbances. The disadvantages of classical sliding mode control are high frequency chattering and poor performance in case of unbounded disturbances. Chattering phenomena is minimized using adaptive fuzzy sliding mode control but fuzzy fixed universe of discourse makes it in-efficient for time varying unbounded disturbances and uncertainties. This article investigates a variable universe of discourse fuzzy logic system for unbounded disturbances. Fuzzy universe of discourse for membership functions of input and output parameters is tuned online using an adaptive empirical law derived from the error dynamics. Performance of proposed control is verified using extensive simulations.

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Periodical:

Applied Mechanics and Materials (Volume 656)

Pages:

327-334

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.656.327

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Online since:

October 2014

Authors:

Nasim Ullah*, Faizan Ahmad Bhatti

Keywords:

Adaptive Control, Fuzzy Logic System, Sliding Mode Control, Unbounded Disturbance Compensation

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] I. Utkin and H. C. Chang, Sliding mode control on electromechanical systems, Mathematical Problems in Engineering. 8 (2002), 451-471.

[2] Kawamura, H. Itoh and K. Sakamoto, Chattering reduction of disturbance observer based sliding mode control, IEEE Transactions on Industry Applications. 30 (1992), 456-461.

DOI: 10.1109/28.287509

[3] H. F. Ho, Y. K. Wong and A. B. Rad, Adaptive fuzzy sliding mode control with chattering elimination for nonlinear SISO systems, Simulation Modeling Practice and Theory. 17(2009), 1199-1210.

DOI: 10.1016/j.simpat.2009.04.004

[4] G. Bartolini, A. Ferrara, E. Usai and V. I. Utkin, On multi-input chattering free second order sliding mode control, IEEE Transactions on Automatic Control. 45(2000), 1711–1717.

DOI: 10.1109/9.880629

[5] G. Bartolini, A. Ferrara and E. Usai, Chattering avoidance by second order sliding mode control, IEEE Transactions on Automatic Control. 43(1998), 241–246.

DOI: 10.1109/9.661074

[6] S. Seshagiri and H. K. Khalil, Robust output feedback regulation of minimum phase nonlinear systems using conditional integrator, Automatica. 41(2005), 43-54.

DOI: 10.1016/s0005-1098(04)00248-1

[7] B. K. Yoo, and W. C. Ham, Adaptive control of robot manipulators using fuzzy compensator, IEEE Transaction on Fuzzy Systems. 8 (2000), 186-199.

DOI: 10.1109/91.842152

[8] Y. Pan, M. J. Er, D. Haung and Q. Wang, Adaptive fuzzy control with guaranteed convergence of optimal approximation error, IEEE Transaction on Fuzzy Systems. 19 (2011), 807-818.

DOI: 10.1109/tfuzz.2011.2144600

[9] N. Ullah, S. Wang and J. Aslam, Adaptive robust control of electrical load simulator based on fuzzy logic compensation, International Conference of Fluid Power and Mechatronics. 2011, 17 – 20, Beijing China.

DOI: 10.1109/fpm.2011.6045882

[10] R. Chen, L. MI and W. Tan, Adaptive fuzzy logic based sliding mode control of electronic throttle, Journal of Computational Information Systems, 8(2012), 3253-3260.

[11] J. Ren and X. Zhang, Compensated tracking errors based adaptive fuzzy controller design for uncertain nonlinear system with minimal parameterization, Journal of Computers. 9(2014), 78-84.

DOI: 10.4304/jcp.9.1.78-84

[12] F. Juntao, W. Shitao, H. Shixi and H. Mingang, A new adaptive fuzzy sliding mode controller for trajectory tracking of MEMS triaxial gyroscope, Proceedings of 31st Chinese Control Conference, 2012, 3482-3487.

[13] J. Becedas, G. Mamani and V. Feliu, Algebraic parameters identification of DC motors methodology and analysis, International Journal of Systems Science. 41(2010), 1241-1255.

DOI: 10.1080/00207720903244097

[14] S. M. Yang and Y. J. Deng, Observer based inertial identification for auto tuning servo motors drive, Industry Applications Conference, 2(2005), 968-972.

DOI: 10.1109/ias.2005.1518467

[16] K. Ohnishsi, N. Matsui, and Y. Hori, Estimation, identification and sensorless control in motion control system, Proceedings of the IEEE. 82(1994), 1253-1263.

DOI: 10.1109/5.301687