Intelligent modeling of double link flexible robotic manipulator using artificial neural network

Journal article


Jamali, A, Mat Darus, IZ, Mohd Samin, PP and Tokhi, MO (2018). Intelligent modeling of double link flexible robotic manipulator using artificial neural network. Journal of Vibroengineering. 20 (2), pp. 1021-1034.
AuthorsJamali, A, Mat Darus, IZ, Mohd Samin, PP and Tokhi, MO
Abstract

The paper investigates the application of the Artificial Neural Network (ANN) in modeling of double-link flexible robotic manipulator (DLFRM). The system was categorized under multi-input multi-output. In this research, the dynamic models of DLFRM were separated into single-input single-output in the modeling stage. Thus, the characteristics of DLFRM were defined separately in each model and the coupling effect was assumed to be minimized. There are four discrete SISO model of double link flexible manipulator were developed from torque input to the hub angle and from torque input to the end point accelerations of each link. An experimental work was established to collect the input-output data pairs and used in developing the system model. Since the system is highly nonlinear, NARX model was chosen as the model structure
because of its simplicity. The nonlinear characteristic of the system was estimated using the ANN whereby multi-layer perceptron (MLP) and ELMAN neural network (ENN) structure were utilized. The implementation of the ANN and its’ effectiveness in developing the model of DLFRM was emphasized. The performance of the MLP was compared to ENN based on the validation of the mean-squared error (MSE) and correlation tests of the developed models. The results indicated that the identification of the DLFRM system using the MLP outperformed the ENN with lower mean squared prediction error and unbiased results for all the models. Thus, the MLP provides a good approximation of the DLFRM dynamic model compared to the ENN.

KeywordsDouble-link flexible manipulator; Flexible manipulator; Artificial neural network; Non-parametric modeling
Year2018
JournalJournal of Vibroengineering
Journal citation20 (2), pp. 1021-1034
PublisherJVE International
ISSN1392-8716
Digital Object Identifier (DOI)doi:10.21595/jve.2017.18575
Publication dates
Print31 Mar 2018
Publication process dates
Deposited11 Jan 2019
Accepted28 Dec 2017
Accepted author manuscript
License
CC BY 4.0
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https://openresearch.lsbu.ac.uk/item/86v88

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