Sliding Mode Control for Flexible-link Manipulators Based on Adaptive Neural Networks
This paper mainly focuses on designing a sliding mode boundary controller for a single flexible-link manipulator based on adaptive radial basis function (RBF) neural network. The flexible manipulator in this paper is considered to be an Euler-Bernoulli beam. We first obtain a partial differential equation (PDE) model of single-link flexible manipulator by using Hamiltons approach. To improve the control robustness, the system uncertainties including modeling uncertainties and external disturbances are compensated by an adaptive neural approximator. Then, a sliding mode control method is designed to drive the joint to a desired position and rapidly suppress vibration on the beam. The stability of the closed-loop system is validated by using Lyapunov’s method based on infinite dimensional model, avoiding problems such as control spillovers caused by traditional finite dimensional truncated models. This novel controller only requires measuring the boundary information, which facilitates implementation in engineering practice. Favorable performance of the closed-loop system is demonstrated by numerical simulations.
KeywordsSliding mode control adaptive control neural network flexible manipulator partial differential equation (PDE)
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The authors would like to thank the Editor-in-Chief, the Associate Editor, and the anonymous reviewers for their constructive comments, which helped to improve the quality and presentation of this paper.
- T. Sangpet, S. Kuntanapreeda, R. Schmidt. Hysteretic nonlinearity observer design based on Kalman filter for piezoactuated flexible beams with control applications. International Journal of Automation and Computing, vol. 11, no. 6, pp. 627–634, 2014. DOI: 10.1007/s11633-014-0817-2.CrossRefGoogle Scholar
- W. He, T. T. Meng, D. Q. Huang, X. F. Li. Adaptive boundary iterative learning control for an Euler-Bernoulli beam system with input constraint. IEEE Transactions on Neural Networks and Learning Systems, to be published. DOI: 10.1109/TNNLS.2017.2673865.Google Scholar
- B. Z. Guo, F. F. Jin. The active disturbance rejection and sliding mode control approach to the stabilization of the Euler-Bernoulli beam equation with boundary input disturbance. Automatica, vol. 49, no. 9, pp. 2911–2918, 2013. DOI: 10.1016/j.automatica.2013.06.018.MathSciNetCrossRefMATHGoogle Scholar
- F. Duarte, F. Ullah, C. Bohn. Modeling and dual loop sliding mode control of a two flexible-link robot to reduce the transient response. In Proceedings of the 24th Mediterranean Conference on Control and Automation, IEEE, Athens, Greece, pp. 280–284, 2016. DOI: 10.1109/MED.2016.7536066.Google Scholar
- A. Mujumdar, S. Kurode, B. Tamhane. Fractional order sliding mode control for single link flexible manipulator. In Proceedings of IEEE International Conference on Control Applications, IEEE, Hyderabad, India, pp. 288–293, 2013. DOI: 10.1109/CCA.2013.6662773.Google Scholar
- S. Kurode, P. Dixit. Output feedback control of flexible link manipulator using sliding modes. In Proceedings of the 7th International Conference on Electrical & Computer Engineering, IEEE, Dhaka, Bangladesh, pp. 949–952, 2012. DOI: 10.1109/ICECE.2012.6471708.Google Scholar
- L. J. Zhang, J. K. Liu. Nonlinear PDE observer design for a flexible two-link manipulator. In Proceedings of American Control Conference, IEEE, Montreal, Canada, pp. 5336–5341, 2012. DOI: 10.1109/ACC.2012.6314625.Google Scholar
- A. P. Tzes, S. Yurkovich, F. D. Langer. Method for solution of the Euler-Bernoulli beam equation in flexible-link robotic systems. In Proceedings of IEEE International Conference on Systems Engineering, IEEE, Fairborn, USA, pp. 557–560, 1989. DOI: 10.1109/ICSYSE.1989.48736.Google Scholar