SLIDING MODE NEURO-ADAPTIVE CONTROLLER DESIGNED IN DISCRETE TIME FOR MOBILE ROBOTS, 55-63.

Francisco G. Rossomando, Carlos Soria, Eduardo O. Freire, and Ricardo O. Carelli

References

  1. [1] F.G. Rossomando, C. Soria, and R. Carelli, Sliding modeneuro adaptive control in trajectory tracking for mobile robots,Journal of Intelligent & Robotic Systems, 74 (3–4), 2014,931–944.
  2. [2] Y. Yamamoto, Identification and control for nonlinear discretetime systems using a new neural network, Intelligent Systemsand Control, Acta Press, 2007, Proceeding 592, vol. 360592,p. 024.
  3. [3] J. Wang, Z., Qu, M.S. Obeng, and X. Wu, Approximationbased adaptive tracking control of uncertain nonholonomicmechanical systems, Control and Intelligent Systems, 37 (4),2009, 204.
  4. [4] J. Ye, Tracking control of a nonholonomic wheeled mobilerobot using improved compound cosine function neuralnetworks, International Journal of Control, 88 (2), 2015,364–373.
  5. [5] F.G. Rossomando, C. Soria, and R. Carelli, Autonomous mobilerobot navigation using RBF neural compensator, ControlEngineering Practice, 19 (3), 2010, 215–222.
  6. [6] M. Lopez-Franco, E.N. Sanchez, A.Y. Alanis, C. Lopez-Franco,and N. Arana-Daniel, Discrete-time decentralized inverse op-timal neural control combined with sliding mode for mobilerobots, IEEE World Automation Congress (WAC), 2014, 496–501, 2014, doi: 10.1109/WAC.2014.6936014.
  7. [7] Y.-J. Liu, L. Tang, S. Tong, and C.L.P. Chen, Adaptive NNcontroller design for a class of nonlinear MIMO discrete-timesystems, IEEE Transactions on Neural Networks and LearningSystems, 26 (5), 2015, 1007–1018.
  8. [8] Z. Wang, R. Lu, F. Gao, and D. Liu, An indirect data-drivenmethod for trajectory tracking control of a class of nonlin-ear discrete time systems, IEEE Transactions on IndustrialElectronics, 64 (5), 2017, 4121–4129.
  9. [9] F.G. Rossomando and C.M. Soria, Discrete-time sliding modeneuro-adaptive controller for SCARA robot arm, Neural Com-puting and Applications, 2017, 28(12), 3837–3850.
  10. [10] F.G. Rossomando and C.M. Soria, Adaptive neural slidingmode control in discrete time for a SCARA robot arm, IEEELatin America Transactions, 14 (6), 2016, 2556–2564.
  11. [11] F.G. Rossomando and C.M. Soria, Identification and controlof nonlinear dynamics of a mobile robot in discrete time usingan adaptive technique based on neural PID, Neural Computingand Applications, 26 (5), 2015, 1179–1191.
  12. [12] J.J.E. Slotine and W. Li, Applied nonlinear control (UpperSaddle River, NJ: Prentice Hall, 1991).
  13. [13] V. Utkin and J. Shi, Integral sliding mode in systems operat-ing under uncertainty conditions, Proc. 35th IEEE Conf. onDecision and Control, Vol. 4, IEEE, 1996, 4591–4596.
  14. [14] Y.J. Liu, S. Li, S. Tong, and C.L.P. Chen, Neuralapproximation-based adaptive control for a class of nonlinearnonstrict feedback discrete-time systems, IEEE Transactionson Neural Networks and Learning Systems, 99, 1–11 doi:10.1109/TNNLS.2016.2531089.
  15. [15] K.J. ˚Astr¨om and T. H¨agglund, PID Controllers: theory, design,and tuning, Instrument Society of America, Research TrianglePark, NC, 2nd edition, 1995.

Important Links:

Go Back