Abstract

In this paper, an adaptive neural discrete-time (ANDT) fractional-order tracking control scheme is proposed for an unmanned aerial vehicle system with prescribed performance in the presence of system uncertainties and unknown bounded disturbances based on a discrete-time disturbance observer (DTDO). The system uncertainties are handled using neural network (NN) approximation. To compensate for the adverse effects of unknown disturbances, an NN-based DTDO is designed. On the basis of the NN, the designed DTDO and the backstepping technology, an ANDT fractional-order control scheme with prescribed performance is developed. Then, the tracking errors are convergent under the proposed control scheme. Finally, the effectiveness of the proposed discrete-time control scheme is demonstrated by numerical simulation results.

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.