Adaptive Fuzzy Global Non-singular Fast Terminal Sliding Mode Control for delta robot based on parameter optimization of Sparrow Search Algorithm

Abstract

Aiming at the characteristics of nonlinearity, strong coupling and unknown perturbation in the dynamics model of Delta robot under high-speed operation, this paper designs a new Global Non-singular Fast Terminal Sliding Mode Control (GNFTSMC), which avoids the singularity of the traditional terminal sliding mode control. On this basis, Fuzzy Global Non-singular Fast Terminal Sliding Mode Control (FGNFTSMC) is proposed by combining Global Non-singular Fast Terminal Sliding Mode Control with fuzzy system, which is a method of eliminating the chattering of sliding mode controller by using fuzzy logic outputs instead of the reaching control law. To improve the trajectory tracking accuracy, the Adaptive Fuzzy Global Non-singular Fast Terminal Sliding Mode Control (AFGNFTSMC) is proposed by adjusting output gain online through the adaptive fuzzy system. The Sparrow Search Algorithm (SSA) is proposed to optimize the Adaptive Fuzzy Global Non-singular Fast Terminal Sliding Mode Control (AFGNFTSMC) sliding surface parameters and select the optimal sliding surface parameters. Experiments show that applying the Adaptive Fuzzy Global Non-singular Fast Terminal Sliding Mode Control optimized based on the SSA (SSA-AFGNFTSMC) to the Delta robot improves the tracking accuracy, reduces the convergence time and eliminates the controller output chattering.