Neuro-Fuzzy Sliding Mode Control of Inverted Pendulum

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In this paper we develop a robust controller based on sliding mode, neural network and fuzzy logic for the control of a class of under-actuated systems. The stability of the proposed controller is proved with the Lyapunov function method. Simulation results are made on an inverted pendulum.

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432-439

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June 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] M.W. Spong: The control of under-actuated mechanical systems (1st International Conference on Mechatronics, 1994).

Google Scholar

[2] M. Bergerman, Y S. Xu: Robust joint and Cartesian control of under-actuated Manipulator System, ASME Journal of dynamic systems Meas and Control, 118, 3,pp.557-565(1994).

DOI: 10.1115/1.2801180

Google Scholar

[3] J.H. Shin and J.J Lee: Trajectory planning and robust adaptive Control for under-actuated manipulators (IEE Electronics Letters, 34, 17, pp.1705-1706, 1998).

DOI: 10.1049/el:19981191

Google Scholar

[4] F. Mnif and J. Ghommen: Genetic algorithm control for an under actuated System (International Journal of Computational Cognition, 3, 1, pp.12-20, 2005).

Google Scholar

[5] J. Yi and W. Wang: Cascade Sliding-Mode Controller for Large-Scale Under actuated Systems, Proceedings (IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.301-306, 2005).

DOI: 10.1109/iros.2005.1545463

Google Scholar

[6] D. Qian, J. Yi and D. Zhao: Robust Control Using Sliding Mode for a Class of Under-Actuated Systems With Mismatched Uncertainties (Proceedings of the American Control Conference,. pp.5254-5259, 2007).

DOI: 10.1109/robot.2007.363188

Google Scholar

[7] J. Yi and N. Yubazaki: Stabilization fuzzy control of inverted pendulum systems (Artificial Intelligence in Engineering, 2000).

DOI: 10.1016/s0954-1810(00)00007-8

Google Scholar

[8] W. Wang: Adaptive Fuzzy Sliding Mode Control for Inverted Pendulum (Proceedings of the Second Symposium International Computer Science and Computational Technology, 2009).

Google Scholar

[9] C. Kunusch, P. F. Puleston, M. A. Mayosky and J. Riera: Sliding Mode Strategy for PEM Fuel Cells Stacks Breathing Control Using a Super-Twisting Algorithm (IEEE Transactions on Control Systems Technology, VOL. 17, NO. 1, 2009).

DOI: 10.1109/tcst.2008.922504

Google Scholar

[10] M. K. Khan, K. B. Goh and S. K. Spurgeon : Second Order Sliding Mode Control of a Diesel Engine ( Asian Journal of Control, Vol. 5, No. 4, pp.614-619, 2003).

DOI: 10.1111/j.1934-6093.2003.tb00177.x

Google Scholar

[11] I. Boiko and L. Fridman: Analysis of Chattering in Continuous Sliding-Mode Controllers (IEEE Transactions on Automatic Control, VOL. 50, NO. 9, 2005).

DOI: 10.1109/tac.2005.854655

Google Scholar

[12] A. Levant and L. Alelishvili: Transient adjustment of high-order sliding modes (in Proc. of the 7th Scientific Workshop "Variable Structure Systems VSS'2004, Vilanova, Spain, September 6-8, 2004).

Google Scholar

[13] T. S. Jimenez: Diving control a torpedo Autonomous Underwater Vehicle (Doctorate thesis, LIRMM - University of Montpellier II, 2004).

Google Scholar

[14] K.S. Yeung and Y. P. Chen: A new Controller design for manipulators using the theory of variable structure systems (J. IEEE Trans. Automat. Control, 1988).

DOI: 10.1109/9.391

Google Scholar

[15] J. Peng, Y. Wang, S. Wei and Y. Liu: A neural network sliding mode controller with application to robotic manipulator (Proceedings of the 6th world congress on intelligent control and automation, June 21- 23, Dalian, China, 2006).

DOI: 10.1109/wcica.2006.1712729

Google Scholar