Identifying The Dynamic Model of the 2-Link Robots in A Functional Study

Abstract

Over the past few years, neural network algorithms have led to the development of new and powerful tools for identifying and modeling nonlinear systems. This study aims to introduce a new recognition tool based on neural networks and strengthen its efficiency as a new recognition method. Also, the developed neural network-based tool is used to extract the dynamic model of the guard robot in a functional study. One of the goals of this study is to implement the system recognition algorithm on the 2-link robot to achieve its dynamic model. To do this, least squares and recursive least squares algorithms and neural networks were used and the results were compared with each other. First, the characteristics of the robot under study are presented, and the modeling and recognition steps are performed on a 2-link robot in MATLAB software. Based on the information and the resulting dynamic equations, the correctness of the performance of the algorithms for use in the recognition of the robot under study was confirmed. Subsequently, all the proposed steps were implemented again for the guard robot.