STRUCTURAL NETWORK MODELING AND CONTROL OF RIGID-BODY ROBOTS

In this paper, two new parametric network models of robots are present ed based on the systems' own functions, The complete dynamics of robot s are given in a ready-to-used format which is constructed by finite d imensional static parametric networks for the inertia matrix and the p otential energy (or the gravitational forces). As a result, dynamic mo dels of robots can be automatically generated by software once given t he number of degrees of freedom (DOF) and the sequence of the joint ty pes, without knowing other parameters such as the lengths and the twis t angles of the links. An existing adaptive controller is used as an e xample to show that some of the controllers can be easily modified suc h that adaptive controllers can be automatically generated. It is show n that all the closed-loop signals are bounded and tracking error goes to zero.