DYNAMIC MODELING AND INTELLIGENT CONTROL OF A 5-DOF ROBOTIC ARM USING ANN-BASED DECOUPLING STRATEGY

Abstract

This paper presents a dynamic model and intelligent control strategy for a four-degree-of-freedom (5-DOF) robotic arm using the Lagrange-Euler formulation. The system consists of five interconnected links, each with independent joint motion subject to strong coupling dynamics. To address these interactions, a decoupling method is implemented using an Artificial Neural Network Inverse Model (ANNIM), enabling accurate trajectory control. The robotic arm’s motion planning focuses on picking and placing tasks, with each link’s angular displacement regulated independently. Simulation results validated the effectiveness of the decoupling approach, demonstrating precise endpoint positioning and robust joint regulation under complex motion scenarios.