AMM-Based Dynamic Modeling and PSO-Optimized FOPID Control for Vibration Suppression in a Two-Link Flexible Manipulator

Abstract

Modern industrial and space applications increasingly utilize flexible robotic manipulators due to their lightweight structure, high speed, and energy efficiency. However, their inherent flexibility introduces structural vibrations and nonlinear dynamics, making control design challenging. This paper presents the dynamic modeling, control design, and optimization of a two-link flexible manipulator. The system dynamics are modeled using the Assumed Modes Method (AMM). A Fractional-Order PID (FOPID) controller is employed as the control architecture, and its performance is compared with an optimized classical PID controller. The controller parameters are optimized using Particle Swarm Optimization (PSO). The PSO algorithm is developed by minimizing an Integral Time Absolute Error (ITAE) cost function. The results demonstrate that the FOPID controller reduces the tip deflection by up to 58 percent, improves the settling time by more than 40 percent, and reduces excessively high-frequency vibrations due to nonlinear coupling between the links. The results show that fractional-order control is more effective for vibration mitigation and offers a solution for advanced robotic applications in industrial and space settings.