Title :
Dynamic Modelling of a Single-Link Flexible Manipulator Using Parametric Techniques with Genetic Algorithms
Author :
Zain, B. A Md ; Tokhi, M.O. ; Salleh, S. Md
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK
Abstract :
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.
Keywords :
autoregressive moving average processes; genetic algorithms; least squares approximations; manipulators; recursive estimation; autoregressive moving average; end-point acceleration; genetic algorithms; mean-squared error; one-step-ahead prediction; parametric techniques; recursive least squares; single-link flexible manipulator; Acceleration; Accelerometers; Autoregressive processes; Genetic algorithms; Manipulator dynamics; Predictive models; Resonance light scattering; Shafts; Torque; Velocity measurement; Genetic Algorithm; Hybrid GARLS; Recursive Least Square; Single-link Flexible Manipulator;
Conference_Titel :
Computer Modeling and Simulation, 2009. EMS '09. Third UKSim European Symposium on
Conference_Location :
Athens
Print_ISBN :
978-1-4244-5345-0
Electronic_ISBN :
978-0-7695-3886-0
DOI :
10.1109/EMS.2009.85
