Parameter Identification of Flexible-Link Manipulators Using Evolutionary Algorithms

This paper addresses the parameter identification of a one-link flexible manipulator based on the experimental measurement of inputs/outputs, the finite element model, and the application of evolutionary algorithms.

A novel approach is proposed to find the inertia, stiffness, and damping parameters by minimizing the difference between the numerical model's outputs and the testbed's outputs, considering the joint position and acceleration of the link's tip. The flexible manipulator's instrumentation, data acquisition, and actuation uses the NI myRIO board to control the XM430-W350 Dynamixel servomotor, and the U2D2 interface couples the servomotor and the NI myRIO board. The accelerometer MMA7361 is connected to the input of the A/D (analog-todigital converter). The programs of NI myRIO are coded using LabVIEW. The dynamic model is initially obtained using the finite element method and the Lagrange principle. Then, an optimization problem minimizes the difference between numerical and experimental outputs to determine the set of parameters using evolutionary algorithms. A comparative analysis to obtain the identified parameters is established using genetic algorithms, particle swarm optimization, and differential evolution.

The proposed identification approach permitted the determination of the dynamic parameters based on the complete dynamic model of the flexible-link manipulator, which is different from the approaches reported in the literature that identify a simplified model. This information is essential for the design of the motion and vibration control laws.