Abstract:
Robotic arms are very powerful machines that can be used in many various applications in industry. So that, a suitable dynamic model is derived to verify that performs th...Show MoreMetadata
Abstract:
Robotic arms are very powerful machines that can be used in many various applications in industry. So that, a suitable dynamic model is derived to verify that performs the tasks. But, dynamic equation is an important issue due to its complexity. Thus, an alternative model can be derived for the robotic arms. This paper is proposed Extreme Learning Machine (ELM) model for the angular acceleration of a robotic arm. The performance of the ELM model is performed by using Pumadyn datasets. At the same time, the validation of the proposed model is compared with Artificial Neural Network (ANN). Experimental results show that the proposed model is suitable and it provides low computation complexity.
Published in: 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR)
Date of Conference: 29 August 2016 - 01 September 2016
Date Added to IEEE Xplore: 26 September 2016
ISBN Information: