Abstract

In this work, an actuator fault tolerant control scheme is developed for a class of uncertain single-input and single-output (SISO) nonlinear systems with the actuator fault. To develop the actuator fault tolerant control scheme, the radial basis function neural network (RBFNN) is employed to approximate the unknown system uncertainties as an universal approximator. Based on bakstepping method, the actuator fault tolerant control scheme is proposed for uncertain nonlinear systems via utilizing the output of the RBFNN. The closed-loop stability is rigorously proved under the developed adaptive fault tolerant control scheme via Lyapunov analysis and the ultimately bounded convergence of all closed-loop signals is guaranteed. Simulation results are given to show the effectiveness of the proposed actuator fault tolerant control scheme.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.