Abstract

This paper develops a design method of recurrent fuzzy neural network (RFNN) control system for multi-input multi-output (MIMO) dynamic systems. This control system consist a feedback controller and a RFNN controller. The feedback controller reveals basic stabilizing controller to stabilize the system and the RFNN controller presents a robust controller to deal with unknown part of system dynamics. The adaptive laws of RFNN are derived based on the Lyapunov stability function so that the stability of the system can be guaranteed. Finally, the proposed control system is applied to an F-16 flight control system. Simulation results demonstrate that the developed control system can achieve favorable robust control performances even with some failures of the flight control system.

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.