Neural Network Sliding Mode Control of 5DOFs Robotic Manipulator

Chang Kai Xu; Ming Li; Jian Yin

doi:10.4028/www.scientific.net/AMR.898.514

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 898Neural Network Sliding Mode Control of 5DOFs...

Neural Network Sliding Mode Control of 5DOFs Robotic Manipulator

Abstract:

In this paper, a neural network sliding mode controller for a kind of 5DOFs robotic manipulator is proposed. A radial basis function (RBF) neural network is used as an estimator to approximate uncertainties of the system. The learning algorithm of the neural network improves the performance of the system. A globle terminal sliding mode control (GTSMC) is designed to guarantee the stability and improve the dynamic performance of the robotic manipulator. Simulation results show that the proposed NNSMC strategy is effective to ensure the robustness and dynamic performance of the 5DOFs robotic manipulator.

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Periodical:

Advanced Materials Research (Volume 898)

Pages:

514-520

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.898.514

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Online since:

February 2014

Authors:

Chang Kai Xu*, Ming Li, Jian Yin

Keywords:

5DOFs Robotic Manipulator, Globle Terminal Sliding Mode Control, RBF Neural Network

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* - Corresponding Author

References

[1] Yaonan Wang. Intelligent Control Engineering for Robotic, Beijing: Technology Press. (2004).

Google Scholar

[2] S. Mahjoub, F. Mnif, N. Derbel, A Sliding mode control applied to whirling pendulum, International Conference on Signals Circuits and Systems (SCS'08) Hammamet, Tunisia, 2008, pp.1-6.

DOI: 10.1109/icscs.2008.4746910

Google Scholar

[3] S. T. Venkataraman, S. Gulati, Control of nonlinear systems using terminal sliding modes, J. Dyn. Syst. Meas. Control, 1993, vol. 115, no. 3, p.554–560.

DOI: 10.1115/1.2899138

Google Scholar

[4] Z. H. Man, A. P. Paplinski, H. R. Wu, A robust MIMO terminal sliding mode control scheme for rigid robotic manipulator, IEEE Tans. Autom. Control, 1994, vol. 39, no. 12, p.2464–2469.

DOI: 10.1109/9.362847

Google Scholar

[5] Y. Tang, Terminal sliding mode control for rigid robots, Automatica, 1998, vol. 34, no. 1, p.51–56.

DOI: 10.1016/s0005-1098(97)00174-x

Google Scholar

[6] K. -B. Park, J. -J. Lee, Comments on A robust MIMO terminal sliding mode control scheme for rigid robotic manipulators, IEEE Trans. Autom. Control, 1996, vol. 41, no. 5, p.761–762.

DOI: 10.1109/9.489220

Google Scholar

[7] S. H. Yu, X. H. Yu, Robust global terminal sliding mode control of SISO nonlinear uncertain systems, Proceedings of the 39th IEEE Conference on Decision and Control, 2000, pp.2198-2203.

DOI: 10.1109/cdc.2000.914122

Google Scholar

[8] Mu Xiaojiang, Chen Yangzhou, Neural Sliding Mode Control for Multi-link Robots, Chinese Control and Decision Conference, 2008, pp.3513-3517.

DOI: 10.1109/ccdc.2008.4597983

Google Scholar

[9] Meliksah Ertugrul, Okyay Kaynak, Neural network adaptive sliding mode control and its application to scara type robot manipulator, Proceedings of the 1997 IEEE Intemational Conference on Robotics and Automation Albuquerque, New Mexico, 1997, pp.2932-2937.

DOI: 10.1109/robot.1997.606732

Google Scholar