Adaptive Discrete ZND Models for Tracking Control of Redundant Manipulator

In recent years, many models with high precision for redundant manipulator tracking control have been proposed based on precise kinematics equations. Nevertheless, without precise kinematic equations, developing a model with high precision for tracking control is meaningful. With the help of zeroing neural dynamics (ZND), a continuous ZND model with adaptive Jacobian matrix is obtained. For better computer operation and easier understanding, developing corresponding discrete ZND (DZND) model is also significant. Therefore, two DZND models (termed DZND-I model and DZND-II model) are proposed in this article on the basis of two discretization formulas, respectively. Meanwhile, theoretical analyses are conducted to ensure the efficacy of DZND-I model and DZND-II model. Finally, the efficacy of the two DZND models with adaptive Jacobian matrix is substantiated by experimental results on the basis of the four-link manipulator, UR5 manipulator, and Jaco2 manipulator, respectively.