NDLI: Robot Manipulator Identification based on a Customized Neural Network & Close Form Differential Equation

Content Provider	IEEE Xplore Digital Library
Author	Nahapetian, N. Motlagh, M. Analoui, M.
Copyright Year	2008
Description	Author affiliation: Comput. Eng. Dept., Iran Univ. of Sci. & Technol., Tehran (Motlagh, M.; Analoui, M.) \|\| Dept. of Comput. Eng., Iran Univ. of Sci. & Technol., Tehran (Nahapetian, N.)
Abstract	In this paper we try to explore the potential of using dynamic neural network approaches to identify the internal behavior of structure-unknown non-linear time variant dynamic systems. We suppose that simple structure or a close form of plant differential equations is available. These types of identifications typically encountered in the field of applied mechanics where the system behavior is fully dynamic and describe by differential equations. In this work, we use the relevant characteristics of recurrent neural networks in serial-parallel topology fashion. Some additional derivation vector of plant input/output driven from the plant differential equation is used as additional input to the network. The network consists of two isolated sections combined with a single neuron. It is shown that, using this topology, the error rate of modeling has been decreased and therefore the identifier performance and resolution increase to the levels reported in others works. We use industrial robot manipulator for the case study in this work. The manipulator is simulated with professional simulation software (consist of solidwork, visual nastran 4D and matlab/simulink).
Starting Page	42
Ending Page	46
File Size	5472436
Page Count	5
File Format	PDF
ISBN	9781424423675
DOI	10.1109/MESA.2008.4735742
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Solid modeling Recurrent neural networks Network topology Error analysis Neural networks Neurons Differential equations Nonlinear dynamical systems Robots Manipulator dynamics
Content Type	Text
Resource Type	Article

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