Radial basis function neural network control for parallel spatial

Received Dec 9, 2019 Revised May 30, 2020 Accepted Jun 25, 2020 Keywords: Inverse dynamics controller Kronecker product Numerical simulation Parallel robot manipulator RBF neural network control ABSTRACT The derivation of motion equations of constrained spatial multibody system is an important problem of dynamics and control of parallel robots. [...]numerical simulation of the inverse dynamics controller for a 3-RRR delta robot manipulator is presented as an illustrative example. [...]the application of modern control methods such as sliding mode control method, the radial basis function (RBF) neural network control method for controller design of the spatial parallel robot manipulators is a new problem that has not been investigated. According to Stone-Weierstrass theorem [23-24] one can choose an appropriate artifical neural network (ANN) with a limited number of neurals that can approximate an unknown nonlinear function with a given accuracy.