UVMS Trajectory Tracking Based on RBFNN and Sliding Mode Control

Huiyi Luo, Weilin Luo, Yuanjing Wang

TL;DR: UVMS Trajectory Tracking Based on RBFNN and Sliding Mode Control

Abstract: This article spells out the UVMS trajectory tracking control problem under electric drive. Firstly, based a claim on Radial Basis Function Neural Networks (RBFNN) and Nonsingular Fast Terminal Sliding Mode (NFTSM) methods, the tracking strategy for UVMS is designed. Further, for singularity problem, a saturation-based tracking controller is obtained by means of the methods mentioned above. Lyapunov design is adopted to guarantee the asymptotic stability of the proposed controller. Simulation results show that the tracking consequence of NN-NFTSM is more thoroughly than PD approach and NN approach. The validity and advantages of the proposed controller is testified.

Submission Number: 10