New-Type DTZ Model for Solving Discrete Time-Dependent Nonlinear Equation System With Robotic-Arm Application

Abstract

In this study, a cubic-precision discretization (CPD) formula is utilized to approximate the first-order time derivative and discretize the continuous-time zeroing model, which is designed via zeroing neural dynamics. Then, a new-type discrete-time zeroing (N-DTZ) model is proposed to solve a special kind of discrete time-dependent problems, that is, discrete time-dependent nonlinear equation system with future unknownness (DT-NES-FU). Comparative numerical experiments, including an application example to the real-time motion generation of a universal two-link robotic arm, are performed to illustrate the superior computational performance of the proposed N-DTZ model for solving the DT-NES-FU, as compared with the presented other models. Finally, detailed comparisons with other types of approximation formulas and the resultant DTZ models further verify the validity and superiority of the presented CPD formula as well as the N-DTZ model for solving the DT-NES-FU.