Theoretics of Zhang Neurodynamics Models for Position-Orientation Control of Soft Continuum Robots from Kinematic Modeling to Noise Suppression

Compared with conventional redundant robots, soft continuum robots (simply termed soft robots or continuum robots) are more flexible, so they have broad application prospects in the future. Although there are a few studies focused on the position-orientation tracking control of soft continuum robots, most of those studies are based on continuous mod-els/algorithms and may have poor effectiveness in noisy environments. Generally, discrete models/algorithms are more friendly to the digital computer, chip, and so on. Hence, developing a discrete, effective, and robust model for the position-orientation tracking control of soft continuum robots is meaningful and significant. In this paper, we first introduce the kinematic modeling process about a three-section soft robot. Then, we use Zhang neurodynamics (ZN) method and develop a continuous ZN (CZN) model. By applying three time-discretization formulas to discretize the CZN model, three discrete ZN (DZN) algorithms are developed for convenient control purposes. We also consider noise situations. Through formulas and detailed theoretical analyses, we prove that three DZN algorithms have great abilities under noise situations.