MATHEMATICAL MODELING OF  8-DEGREE-OF-FREEDOM ROBOTIC ARM USING LAGRANGE-EULER DYNAMICS AND NEURAL NETWORK CONTROLLER

Authors

  • Eze Ukamaka. J. Dept. of Computer Engineering, Madonna University, Akpugo Campus, Enugu State, Nigeria, 
  • Ndubuisi Paul-Darlington Ibemezie Federal Polytechnic Ngodo-Isuochi, Abia State, Nigeria
  • Obi M.C. Dept. of Computer Engineering, Caritas University, Enugu, Nigeria

Keywords:

8-DOF Robotic Arm, Artificial Neural Networks (ANN), Intelligent Control, Mathematical Modeling, Joint Trajectory Tracking, Inverse Kinematics, Decoupled Joint Control

Abstract

This study presents a comprehensive mathematical modeling of 8-Degree-of-Freedom (8-DOF) robotic arm using the Lagrange-Euler formulation combined with intelligent control techniques. The robotic system, composed of eight revolute joints and corresponding links, exhibits nonlinear, coupled dynamics that complicate control and trajectory tracking. To overcome these challenges, this paper proposes a hybrid control strategy integrating kinematic and dynamic modeling with Artificial Neural Network Inverse Modeling (ANNIM) for improved motion control and precision. The resulting system is simulated, and results confirmed that decoupling and neural network-based training allowed for independent joint control and enhanced speed performance in complex trajectory scenarios.

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Published

2026-03-24

Issue

Vol. 1 No. 1 (2026): INTERNATIONAL RESEARCH JOURNAL OF ENGINEERING AND COMPUTING SCIENCES (IRJECS) MARCH 2026

Section

Articles