Dynamic Modelling of a Single-Link Flexible Manipulator Using Parametric Techniques with Genetic Algorithms

This paper presents development of an approach with recursive least squares (RLS) and genetic algorithms (GAs) for modelling of single-link flexible manipulators. Investigations focus on modelling the system from input torque to hub-angle, hub-velocity and end-point acceleration outputs. Both GA and combined GA and RLS (GARLS) are used to model the system using the autoregressive moving average (ARMA) model structure with one-step-ahead prediction. The mean-squared error (MSE) of the output is used as the fitness function Results are presented using data collected from an experimental flexible manipulator rig, and a comparative assessment of the GA, RLS and GARLS approaches in modelling the system is presented and discussed.