Departamento de Ingeniería Eléctrica

Facultad de Ingeniería
Universidad de Santiago de Chile

Dr. Claudio Urrea y José Pascal publican artículo WoS en journal Computers & Electrical Engineering

Oct
13
2016

Dr. Claudio Urrea y José Pascal publican artículo WoS titulado "Design, Simulation, Comparison and Evaluation of Parameter Identification Methods for an Industrial Robot", en journal Computers & Electrical Engineering. Print ISSN: 0045-7906; Electronic ISSN: 1879-0755. DOI: 10.1016/j.compeleceng.2016.09.004

ABSTRACT

This study discusses the design and assessment of different parameter identification methods applied to robot systems, such as least squares, extended Kalman filter, Adaptive Linear Neuron (Adaline) neural networks, Hopfield recurrent neural networks and genetic algorithms. First, the characteristics of the methods above mentioned are described. Second, using the software MatLab/Simulink, a simulation of a Selective Compliant Assembly Robot Arm (SCARA) robot with 3 Degrees of Freedom (DOF) is carried out by applying these parameter identification methods, thereby obtaining the performance indicators of the algorithms that allow for parameter identification. Therefore, this study enables the adequate selection of identification methods to obtain parameters that characterize the dynamics of industrial robots, particularly of the SCARA type. Hence, having the values of the base parameters of a robot contributes to the design of new control methods, since the robot characteristic dynamic model is known.

KEYWORDS

System identification; dynamical systems; mathematical model; robotics.

Este artículo puede ser descargado directamente desde:

http://www.sciencedirect.com/science/article/pii/S0045790616302294