Neural Network and Performance Analysis for a Novel Reconfigurable Parallel Manipulator Based on the Spatial Multiloop Overconstrained Mechanism

Abstract

To meet the different requirements in the industrial area, a novel reconfigurable parallel mechanism is proposed based on the spatial multiloop overconstrained mechanism. The configurations can be changed by driving the low-DOF (degree-of-freedom) overconstrained mechanism. The mobility of this mechanism is investigated. And the kinematic model and Jacobian matrix are both established. Based on the Jacobian matrix, the workspace, stiffness, and conditional number are all analyzed. To focus on the application in the industrial area, this paper proposes a method to establish the relationship between the performance and the structural parameters by using the modified BP neural network. Based on this method, the structural parameters can be chosen by the requirements of the special task in the industrial area. Finally, some numerical examples are presented to verify the method.