Open Access
Issue
MATEC Web Conf.
Volume 214, 2018
2018 2nd International Conference on Information Processing and Control Engineering (ICIPCE 2018)
Article Number 03005
Number of page(s) 4
Section Electronic Information Technology and Control Engineering
DOI https://doi.org/10.1051/matecconf/201821403005
Published online 15 October 2018
  1. J. Wei, Y. Zhang, H. Bao, An exploration on adaptive iterative learning control for a class of commensurate high-order uncertain nonlinear fractional order systems, IEEE CAA J. Autom. Sin., 5(2) (2018) 618–627. [CrossRef] [Google Scholar]
  2. T. Kaczorek, Positivity and linearization of a class of nonlinear continuous-time systems by state feedbacks, Int. J. Appl. Math. Comput. Sci., 25(4) (2015) 827–831. [CrossRef] [Google Scholar]
  3. W. Lv, F. Wang, Finite-time adaptive fuzzy tracking control for a class of nonlinear systems with unknown hysteresis, Int. J. Fuzzy Syst., 20(3) (2018) 782–790. [CrossRef] [Google Scholar]
  4. J. Zhang, M. Lyu, T. Shen, Sliding mode control for a class of nonlinear multi-agent system with time delay and uncertainties, IEEE Trans Ind Electron, 65(1) (2018) 865–875. [CrossRef] [Google Scholar]
  5. K. Zhu, N.M. Qi, C.M. Qin, Adaptive sliding mode controller design for BTT missile based on backstepping control, Yuhang Xuebao, 31(3) (2010) 769–773. [Google Scholar]
  6. J. Park, I.W. Sandberg, Universal approximation using radial-basis-function networks, Neural Computation, 3(2) (1991): 246–257. [CrossRef] [Google Scholar]
  7. S. Zhang, Z. Wu, An adaptive block backstepping control strategy for motorized spindles based on improved RBF neural network, Boletin Tecnico, 55(9) (2017) 432–439. [Google Scholar]
  8. J. Liu, Radial basis function (RBF) neural network control for mechanical systems: Design, analysis and matlab simulation[M], Germany: Springer-Verlag Berlin Heidelberg, 2013. [CrossRef] [Google Scholar]
  9. W. Si, X. Dong, F. Yang, Decentralized adaptive neural control for high-order stochastic nonlinear strongly interconnected systems with unknown system dynamics, Inf Sci, 424 (2018) 137–158. [CrossRef] [Google Scholar]
  10. Y. Sun, B. Chen, C. Lin, Adaptive neural control for a class of stochastic nonlinear systems by backstepping approach, Inf Sci, 369 (2016) 748–764. [CrossRef] [Google Scholar]
  11. D. Mu, G. Wang, Y. Fan, Design of robust adaptive course controller for unmanned surface vehicle with input saturation, Int. J. Innov. Comput. Inf. Control, 13(5) (2017) 1751–1758. [Google Scholar]
  12. X.J. Ren, R.C. Liu, Y. Chen, Z.Y. Yang, Robust adaptive control for a class of nonlinear systems using backstepping based on RBF neural network, Journal of Naval Aeronautical and Astronautical University, 23(6) (2008) 645–648. [Google Scholar]
  13. Y. Hu, Y. Jin, P. Cui, RBF NN-based backstepping control for strict feedback block nonlinear system and its application, Lect. Notes Comput. Sci., 3174 (2004) 129–137. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.