Adaptive Neural-Fuzzy Sliding-Mode Fault-Tolerant Control for Uncertain Nonlinear Systems Academic Article uri icon


  • 2013 IEEE. This paper proposes an adaptive neural-fuzzy sliding-mode control method for uncertain nonlinear systems with actuator effectiveness faults and input saturation. The parameter dependence of the control scheme is removed from the bound of actuator faults by updating online. A neural-fuzzy model is developed to approximate the uncertain nonlinear terms and a sliding-mode online-updating controller is developed to estimate the bound of the actuator with no prior knowledge of the fault. The asymptotic stability is verified via the Lyapunov method in the presence of actuator faults and saturation. Furthermore, the adaptive neural-fuzzy control method is extended to the uncertain faulty nonlinear systems with integral sliding-mode manifold as well as other popular sliding-mode surfaces. A numerical example is presented to demonstrate the effectiveness of the derived results.

published proceedings


author list (cited authors)

  • Wen, S., Chen, M., Zeng, Z., Huang, T., & Li, C.

citation count

  • 70

complete list of authors

  • Wen, Shiping||Chen, Michael ZQ||Zeng, Zhigang||Huang, Tingwen||Li, Chaojie

publication date

  • August 2017