327
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Neural network-based adaptive asymptotic tracking of nonstrict feedback nonlinear systems with state constraints

, , &
Pages 321-331 | Received 30 Apr 2021, Accepted 27 Sep 2021, Published online: 21 Oct 2021

References

  • Chen, B., Liu, X. P., Ge, S. S., & Lin, C. (2012). Adaptive fuzzy control of a class of nonlinear systems by fuzzy approximation approach. IEEE Transactions on Fuzzy Systems, 20(6), 1012–1021. https://doi.org/10.1109/TFUZZ.2012.2190048
  • Chen, B., Liu, X. P., Liu, K. F., & Lin, C. (2009). Direct adaptive fuzzy control of nonlinear strict-feedback systems. Automatica, 45(6), 1530–1535. https://doi.org/10.1016/j.automatica.2009.02.025
  • Jin, X., & Xu, J. X. (2013). Iterative learning control for output-constrained systems with both parametric and nonparametric uncertainties. Automatica, 49(8), 2508–2516. https://doi.org/10.1016/j.automatica.2013.04.039
  • Krstić, M., Kanellakopoulos, I., & Kokotović, P. V. (1995). Nonlinear and adaptive control design. Wiley.
  • Li, H. Y., Bai, L., Zhou, Q., Lu, R. Q., & Wang, L. J. (2017). Adaptive fuzzy control of stochastic nonstrict-feedback nonlinear systems with input saturation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(8), 2185–2197. https://doi.org/10.1109/TSMC.2016.2635678
  • Li, Y. M., Liu, Y. J., & Tong, S. C. (2021). Observer-based neuro-adaptive optimized control of strict-feedback nonlinear systems with state constraints. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2021.3051030
  • Li, Y. M., & Tong, S. C. (2017a). Adaptive fuzzy output constrained control design for multi-input multi-output stochastic nonstrict-feedback nonlinear systems. IEEE Transactions on Cybernetics, 47(12), 4086–4095. https://doi.org/10.1109/TCYB.2016.2600263
  • Li, Y. M., & Tong, S. C. (2017b). Adaptive neural networks decentralized FTC design for nonstrict-feedback nonlinear interconnected large-scale systems against actuator faults. IEEE Transactions on Neural Networks and Learning Systems, 28(11), 2541–2554. https://doi.org/10.1109/TNNLS.2016.2598580
  • Li, Y. M., Wang, T. C., Liu, W., & Tong, S. C. (2021). Neural network adaptive output-feedback optimal control for active suspension systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems. https://doi.org/10.1109/TSMC.2021.3089768.
  • Li, Y. X. (2020). Barrier Lyapunov function-based adaptive asymptotic tracking of nonlinear systems with unknown virtual control coefficients. Automatica, 121, 109–118. https://doi.org/10.1016/j.automatica.2020.109181
  • Li, Y. X., & Yang, G. H. (2016). Adaptive asymptotic tracking control of uncertain nonlinear systems with input quantization and actuator faults. Automatica, 72(7), 177–185. https://doi.org/10.1016/j.automatica.2016.06.008
  • Liang, Y. J., Li, Y. X., Che, W. W., & Hou, Z. S. (2021). Adaptive fuzzy asymptotic tracking for nonlinear systems with nonstrict-feedback structure. IEEE Transactions on Cybernetics, 51(2), 853–861. https://doi.org/10.1109/TCYB.6221036
  • Liu, L., Gao, T. T., Liu, Y. J., Tong, S. C., Chen, C. L. P., & Ma, L. (2021). Time-varying IBLFs-based adaptive control of uncertain nonlinear systems with full state constraints. Automatica, 129(5), 109595. https://doi.org/10.1016/j.automatica.2021.109595
  • Liu, L., Li, X. S., Liu, Y. J., & Tong, S. C. (2021). Neural network based adaptive event trigger control for a class of electromagnetic suspension systems. Control Engineering Practice, 106(6), 104675. https://doi.org/10.1016/j.conengprac.2020.104675
  • Liu, L., Liu, Y. J., Chen, A. Q., Tong, S. C., & Chen, C. L. P. (2020). Integral barrier Lyapunov function-based adaptive control for switched nonlinear systems. Science China Information Sciences, 63(3), 132203:1–132203:14. https://doi.org/10.1007/s11432-019-2714-7
  • Liu, Y., Yao, D. Y., Li, H. Y., & Lu, R. Q. (2020). Distributed cooperative compound tracking control for a platoon of vehicles with adaptive NN. IEEE Transactions on Cybernetics. https://doi.org/10.1109/TCYB.2020.3044883.
  • Liu, Y. C., & Zhu, Q. D. (2021). Adaptive fuzzy finite-time control for nonstrict-feedback nonlinear systems. IEEE Transactions on Cybernetics, https://doi.org/10.1109/TCYB.2021.3063139.
  • Liu, Y. J., & Tong, S. C. (2017). Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems. Automatica, 76(1–4), 143–152. https://doi.org/10.1016/j.automatica.2016.10.011
  • Liu, Z., Lai, G. Y., Zhang, Y., & Chen, C. L. P. (2015). Adaptive fuzzy tracking control of nonlinear time-delay systems with dead-zone output mechanism based on a novel smooth model. IEEE Transactions on Fuzzy Systems, 23(6), 1998–2011. https://doi.org/10.1109/TFUZZ.2015.2396075
  • Liu, Z. L., Chen, B., & Lin, C. (2017). Adaptive neural backstepping for a class of switched nonlinear system without strict-feedback form. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(7), 1315–1320. https://doi.org/10.1109/TSMC.2016.2585664
  • Ma, L., & Liu, L. (2021). Adaptive neural network control design for uncertain nonstrict feedback nonlinear system with state constraints. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(6), 3678–3686. https://doi.org/10.1109/TSMC.6221021
  • Slotine, J. J., & Li, W. P. (1991). Applied nonlinear control. Prentice-Hall.
  • Sun, W., Su, S. F., Wu, Y. Q., Xia, J. W., & Nguyen, V. T. (2020). Adaptive fuzzy control with high-order barrier Lyapunov functions for high-order uncertain nonlinear systems with full-state constraints. IEEE Transactions on Cybernetics, 50(8), 3424–3432. https://doi.org/10.1109/TCYB.6221036
  • Tee, K. P., & Ge, S. S. (2011). Control of nonlinear systems with partial state constraints using a barrier Lyapunov function. International Journal of Control, 84(12), 2008–2023. https://doi.org/10.1080/00207179.2011.631192
  • Tee, K. P., & Ge, S. S. (2012). Control of state-constrained nonlinear systems using integral barrier Lyapunov functionals. In 2012 IEEE 51st IEEE Conference on Decision and Control (pp. 3239–3244). IEEE.
  • Tee, K. P., Ge, S. S., & Tay, E. H. (2009). Barrier Lyapunov functions for the control of output-constrained nonlinear systems. Automatica, 45(4), 918–927. https://doi.org/10.1016/j.automatica.2008.11.017
  • Tong, S. C., Li, Y. M., & Sui, S. (2016). Adaptive fuzzy tracking control design for SISO uncertain nonstrict feedback nonlinear systems. IEEE Transactions on Fuzzy Systems, 24(6), 1441–1454. https://doi.org/10.1109/TFUZZ.2016.2540058
  • Tong, S. C., Min, X., & Li, Y. X. (2020). Observer-based adaptive fuzzy tracking control for strict-feedback nonlinear systems with unknown control gain functions. IEEE Transactions on Cybernetics, 50(9), 3903–3913. https://doi.org/10.1109/TCYB.6221036
  • Wang, C. L., & Lin, Y. (2012). Multivariable adaptive dynamic surface control based on norm estimation of unknown parameter matrices. International Journal of Control, 85(12), 1827–1837. https://doi.org/10.1080/00207179.2012.704402
  • Wang, H. Q., Liu, K. F., Liu, X. P., Chen, B., & Lin, C. (2015). Neural-based adaptive output-feedback control for a class of nonstrict-feedback stochastic nonlinear systems. IEEE Transactions on Cybernetics, 45(9), 1977–1987. https://doi.org/10.1109/TCYB.2014.2363073
  • Wang, M., Wang, C., & Liu, X. P. (2014). Dynamic learning from adaptive neural control with predefined performance for a class of nonlinear systems. Information Sciences, 279, 874–888. https://doi.org/10.1016/j.ins.2014.04.038
  • Wang, X. J., Niu, B., Zhao, P., & Song, X. M. (2021). Neural networks-based adaptive finite-time prescribed performance fault-tolerant control of switched nonlinear systems. International Journal of Adaptive Control and Signal Processing, 35(4), 532–548. https://doi.org/10.1002/acs.v35.4
  • Wen, G. X., Ge, S. S., & Tu, F. W. (2018). Optimized backstepping for tracking control of strict-feedback systems. IEEE Transactions on Neural Networks and Learning Systems, 29(3), 3850–3862. https://doi.org/10.1109/TNNLS.2018.2803726
  • Yang, C. G., Li, Y. N., Ge, S. S., & Lee, T. H. (2010). Adaptive control of a class of discrete-time MIMO nonlinear systems with uncertain couplings. International Journal of Control, 83(10), 2120–2133. https://doi.org/10.1080/00207179.2010.508092
  • Zhang, Z. Q., & Xie, X. J. (2014). Asymptotic tracking control of uncertain nonlinear systems with unknown actuator nonlinearity and unknown gain signs. International Journal of Control, 87(11), 2294–2311. https://doi.org/10.1080/00207179.2014.909948
  • Zhao, N., Shi, P., Xing, W., & Jonathon, C. (2021). Observer-based event-triggered approach for stochastic networked control systems under denial of service attacks. IEEE Transactions on Control of Network Systems, 8(1), 158–167. https://doi.org/10.1109/TCNS.6509490
  • Zhou, Q., Li, H. Y., Wang, L. J., & Lu, R. Q. (2017). Prescribed performance observer-based adaptive fuzzy control for nonstrict-feedback stochastic nonlinear systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(10), 1747–1758. https://doi.org/10.1109/TSMC.2017.2738155
  • Zhu, Q. D., Liu, Y. C., & Wen, G. X. (2020a). Adaptive neural network control for time-varying state constrained nonlinear stochastic systems with input saturation. Information Sciences, 527(7), 191–209. https://doi.org/10.1016/j.ins.2020.03.055
  • Zhu, Q. D., Liu, Y. C., & Wen, G. X. (2020b). Adaptive neural network output feedback control for stochastic nonlinear systems with full state constraints. ISA Transactions, 101(1), 60–68. https://doi.org/10.1016/j.isatra.2020.01.021
  • Zong, G. D., Sun, H. B., & Nguang, S. K. (2021). Decentralized adaptive neuro-output feedback saturated control for INS and its application to AUV. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2021.3050992

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.