Robust discrete-time sliding mode control for tracking and model following of uncertain nonlinear systems

References

• Derakhshan, S. F., & Fatehi, A. (2015). Non-monotonic robust H2 fuzzy observer-based control for discrete time nonlinear systems with parametric uncertainties. International Journal of Systems Science, 46(12), 2134–2149. doi: 10.1080/00207721.2013.854941
   Web of Science ®Google Scholar
• Fei, J., & Lu, C. (2018). Adaptive sliding mode control of dynamic systems using double loop recurrent neural network structure. IEEE Transactions on Neural Networks and Learning Systems, 29(4), 1275–1286. doi: 10.1109/TNNLS.2017.2672998
   PubMed Web of Science ®Google Scholar
• Hopp, T. H., & Schmitendorf, W. E. (1990). Design of a linear controller for robust tracking and model following. ASME: Journal of Dynamic Systems, Measurement, and Control, 112, 552–558.
   Web of Science ®Google Scholar
• Kim, D. W., Lee, H. J., & Tomizuka, M. (2010). Fuzzy stabilization of nonlinear systems under sampled-data feedback: An exact discrete-time model approach. IEEE Transactions on Fuzzy Systems, 18(2), 251–260.
   Web of Science ®Google Scholar
• Liu, Y. J., & Tong, S. (2015). Adaptive NN tracking control of uncertain nonlinear discrete-time systems with nonaffine dead-zone input. IEEE Transactions on Cybernetics, 45(3), 497–505. doi: 10.1109/TCYB.2014.2329495
   PubMed Web of Science ®Google Scholar
• Liu, M., Zhang, S., Chen, H., & Sheng, W. (2014). H∞ output tracking control of discrete-time nonlinear systems via standard neural network models. IEEE Transactions on Neural Networks and Learning Systems, 25(10), 1928–1935. doi: 10.1109/TNNLS.2013.2295846
   PubMed Web of Science ®Google Scholar
• Long, S., Zhong, S., Zhu, H., & Xiong, L. (2014). Delay-dependent stochastic admissibility for a class of discrete-time nonlinear singular Markovian jump systems with time-varying delay. Communications in Nonlinear Science and Numerical Simulation, 19(3), 673–685. doi: 10.1016/j.cnsns.2013.07.014
   Web of Science ®Google Scholar
• Majd, V. J., & Mobayen, S. (2015). An ISM-based CNF tracking controller design for uncertain MIMO linear systems with multiple time-delays and external disturbances. Nonlinear Dynamics, 80(1), 591–613. doi: 10.1007/s11071-015-1892-9
   Web of Science ®Google Scholar
• Mobayen, S. (2014). Robust tracking controller for multivariable delayed systems with input saturation via composite nonlinear feedback. Nonlinear Dynamics, 76(1), 827–838. doi: 10.1007/s11071-013-1172-5
   Web of Science ®Google Scholar
• Mobayen, S., & Tchier, F. (2017). A novel robust adaptive second-order sliding mode tracking control technique for uncertain dynamical systems with matched and unmatched disturbances. International Journal of Control, Automation and Systems, 15(3), 1097–1106. doi: 10.1007/s12555-015-0477-1
   Web of Science ®Google Scholar
• Oliveira, M. Z., da Silva Jr., J.G., & Coutinho, D. (2013). Stability analysis for a class of nonlinear discrete-time control systems subject to disturbances and to actuator saturation. International Journal of Control, 86(5), 869–882. doi: 10.1080/00207179.2013.765036
   Web of Science ®Google Scholar
• Pai, M. C. (2013). Robust tracking and model following based on discrete-time neuro-sliding mode control for uncertain time-delay systems. Nonlinear Dynamics, 73, 427–437. doi: 10.1007/s11071-013-0798-7
   Web of Science ®Google Scholar
• Pai, M. C. (2015). Dynamic output feedback RBF neural network sliding mode control for robust tracking and model following. Nonlinear Dynamics, 79(2), 1023–1033. doi: 10.1007/s11071-014-1720-7
   Web of Science ®Google Scholar
• Rahmani, B. (2017). Robust output feedback sliding mode control for uncertain discrete time systems. Nonlinear Analysis: Hybrid Systems, 24, 83–99.
   Web of Science ®Google Scholar
• Sahoo, A., Xu, H., & Jagannathan, S. (2016). Adaptive neural network-based event-triggered control of single-input single-output nonlinear discrete-time systems. IEEE Transactions on Neural Networks and Learning Systems, 27(1), 151–164. doi: 10.1109/TNNLS.2015.2472290
   PubMed Web of Science ®Google Scholar
• Salhi, H., Kamoun, S., Essounbouli, N., & Hamzaoui, A. (2016). Adaptive discrete-time sliding-mode control of nonlinear systems described by Wiener models. International Journal of Control, 86(3), 611–622. doi: 10.1080/00207179.2015.1088964
   Web of Science ®Google Scholar
• Sarpturk, S., Istefanopulos, Y., & Kaynak, O. (1987). On the stability of discrete-time sliding mode control systems. IEEE Transactions on Automatic Control, 32(10), 930–932. doi: 10.1109/TAC.1987.1104468
   Web of Science ®Google Scholar
• Sung, H. C., Park, J. B., & Joo, Y. H. (2010). Robust digital control of fuzzy systems with parametric uncertainties: LMI-based digital redesign approach. Fuzzy Sets and Systems, 38(1), 919–933. doi: 10.1016/j.fss.2009.04.016
   Web of Science ®Google Scholar
• Wang, R., & Fei, S. (2015). Output tracking for nonlinear discrete-time systems via fuzzy control approach. Journal of the Franklin Institute, 352(10), 4147–4162. doi: 10.1016/j.jfranklin.2015.06.009
   Web of Science ®Google Scholar
• Wang, J., Gao, Y., Qiu, J., & Ahn, C. K. (2017). Sliding mode control for non-linear systems by Takagi–Sugeno fuzzy model and delta operator approaches. IET Control Theory & Applications, 24, 1205–1213. doi: 10.1049/iet-cta.2016.0231
   Web of Science ®Google Scholar
• Wang, X., Liu, Z., & Cai, Y. (2015). Adaptive single neural network control for a class of uncertain discrete-time nonlinear strict-feedback systems with input saturation. Nonlinear Dynamics, 82(4), 2021–2030. doi: 10.1007/s11071-015-2296-6
   Web of Science ®Google Scholar
• Wei, Q., & Liu, D. (2015). Neural-network-based adaptive optimal tracking control scheme for discrete-time nonlinear systems with approximation errors. Neurocomputing, 149, Part A, 106–115. doi: 10.1016/j.neucom.2013.09.069
   Web of Science ®Google Scholar
• Wei, Q., Liu, D., & Yang, X. (2015). Infinite horizon self-learning optimal control of nonaffine discrete-time nonlinear systems. IEEE Transactions on Neural Networks and Learning Systems, 26(4), 866–879. doi: 10.1109/TNNLS.2015.2401334
   PubMed Web of Science ®Google Scholar
• Xiao, Z., Li, T., & Li, Z. (2015). A novel single fuzzy approximation based adaptive control for a class of uncertain strict-feedback discrete-time nonlinear systems. Neurocomputing, 167, 179–186. doi: 10.1016/j.neucom.2015.04.079
   Web of Science ®Google Scholar
• Xie, L. (1996). Output feedback H∞ control of systems with parameter uncertainty. International Journal of Control, 63(4), 741–750. doi: 10.1080/00207179608921866
   Web of Science ®Google Scholar
• Yazid, Y. B., Mehdi, D., & Nouri, A. S. (2018). Discrete T–S fuzzy systems with time-varying delays: A new discrete sliding mode control approach. Transactions of the Institute of Measurement and Control, 40(7), 2332–2339. doi: 10.1177/0142331217707365
   Web of Science ®Google Scholar
• Yoshimura, T. (2015). Design of a simplified adaptive fuzzy backstepping control for uncertain discrete-time nonlinear systems. International Journal of Systems Science, 46(5), 763–775. doi: 10.1080/00207721.2014.973468
   Web of Science ®Google Scholar
• Yoshimura, T. (2016). Design of an adaptive fuzzy sliding mode control for uncertain discrete-time nonlinear systems based on noisy measurements. International Journal of Systems Science, 47(3), 617–630. doi: 10.1080/00207721.2014.891776
   Web of Science ®Google Scholar
• Zhang, H., Qin, C., Jiang, B., & Luo, Y. (2014). Online adaptive policy learning algorithm for H∞ state feedback control of unknown affine nonlinear discrete-time systems. IEEE Transactions on Cybernetics, 44(12), 2706–2718. doi: 10.1109/TCYB.2014.2313915
   PubMed Web of Science ®Google Scholar
• Zhao, J. (2016). NN-adaptive predictive control for a class of discrete-time nonlinear systems with input-delay. Neurocomputing, 173, Part 3, 1832–1838. doi: 10.1016/j.neucom.2015.09.059
   Web of Science ®Google Scholar
• Zhao, Q., Xu, H., & Jagannathan, S. (2014). Near optimal output feedback control of nonlinear discrete-time systems based on reinforcement neural network learning. IEEE/CAA Journal of Automatica Sinica, 1(4), 372–384. doi: 10.1109/JAS.2014.7004665
   Google Scholar
• Zhao, Q., Xu, H., & Jagannathan, S. (2015). Neural network-based finite-horizon optimal control of uncertain affine nonlinear discrete-time systems. IEEE Transactions on Neural Networks and Learning Systems, 26(3), 486–499. doi: 10.1109/TNNLS.2014.2315646
   PubMed Web of Science ®Google Scholar
• Zhou, Q., Liu, D., Gao, Y., Lam, H. K., & Sakthivel, R. (2015). Interval type-2 fuzzy control for nonlinear discrete-time systems with time-varying delays. Neurocomputing, 157, 22–32. doi: 10.1016/j.neucom.2015.01.042
   Web of Science ®Google Scholar