A new adaptive neural network based observer for robotic manipulators

Reza Mohammadi Asl; Farzad Hashemzadeh; Mohammad Ali Badamchizadeh

doi:10.1109/ICRoM.2015.7367862

A new adaptive neural network based observer for robotic manipulators

Reza Mohammadi Asl, Farzad Hashemzadeh, Mohammad Ali Badamchizadeh

University of Tabriz

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

Abstract

In this paper, a new neural network based observer is proposed for a class of nonlinear systems. The proposed observer can applied to estimate nonlinear systems with a high nonlinearity without any prior knowledge about system. This features help the proposed neuro-observer for real implementation and to use it in practice. The Lyapunov's direct method employed to show the stability and estimating performance of the proposed scheme. Simulation results on a two DOF robot manipulator are presented to show the efficiency of the proposed neural network based observer.

Original language	English
Title of host publication	International Conference on Robotics and Mechatronics, ICROM 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	663-668
Number of pages	6
ISBN (Electronic)	9781467372343
DOIs	https://doi.org/10.1109/ICRoM.2015.7367862
Publication status	Published - 28 Dec 2015
Externally published	Yes
Event	3rd RSI/ISM International Conference on Robotics and Mechatronics, ICROM 2015 - Tehran, Iran, Islamic Republic of Duration: 7 Oct 2015 → 9 Oct 2015

Publication series

Name	International Conference on Robotics and Mechatronics, ICROM 2015

Conference

Conference	3rd RSI/ISM International Conference on Robotics and Mechatronics, ICROM 2015
Country/Territory	Iran, Islamic Republic of
City	Tehran
Period	7/10/15 → 9/10/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Lyapunov stability
Neural Network
neuro-observer
robot manipulator
state observer

Access to Document

10.1109/ICRoM.2015.7367862

Cite this

Asl, R. M., Hashemzadeh, F., & Badamchizadeh, M. A. (2015). A new adaptive neural network based observer for robotic manipulators. In International Conference on Robotics and Mechatronics, ICROM 2015 (pp. 663-668). Article 7367862 (International Conference on Robotics and Mechatronics, ICROM 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRoM.2015.7367862

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abstract = "In this paper, a new neural network based observer is proposed for a class of nonlinear systems. The proposed observer can applied to estimate nonlinear systems with a high nonlinearity without any prior knowledge about system. This features help the proposed neuro-observer for real implementation and to use it in practice. The Lyapunov's direct method employed to show the stability and estimating performance of the proposed scheme. Simulation results on a two DOF robot manipulator are presented to show the efficiency of the proposed neural network based observer.",

keywords = "Lyapunov stability, Neural Network, neuro-observer, robot manipulator, state observer",

author = "Asl, {Reza Mohammadi} and Farzad Hashemzadeh and Badamchizadeh, {Mohammad Ali}",

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year = "2015",

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doi = "10.1109/ICRoM.2015.7367862",

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series = "International Conference on Robotics and Mechatronics, ICROM 2015",

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Asl, RM, Hashemzadeh, F & Badamchizadeh, MA 2015, A new adaptive neural network based observer for robotic manipulators. in International Conference on Robotics and Mechatronics, ICROM 2015., 7367862, International Conference on Robotics and Mechatronics, ICROM 2015, Institute of Electrical and Electronics Engineers Inc., pp. 663-668, 3rd RSI/ISM International Conference on Robotics and Mechatronics, ICROM 2015, Tehran, Iran, Islamic Republic of, 7/10/15. https://doi.org/10.1109/ICRoM.2015.7367862

A new adaptive neural network based observer for robotic manipulators. / Asl, Reza Mohammadi; Hashemzadeh, Farzad; Badamchizadeh, Mohammad Ali.
International Conference on Robotics and Mechatronics, ICROM 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 663-668 7367862 (International Conference on Robotics and Mechatronics, ICROM 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hashemzadeh, Farzad

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PY - 2015/12/28

Y1 - 2015/12/28

N2 - In this paper, a new neural network based observer is proposed for a class of nonlinear systems. The proposed observer can applied to estimate nonlinear systems with a high nonlinearity without any prior knowledge about system. This features help the proposed neuro-observer for real implementation and to use it in practice. The Lyapunov's direct method employed to show the stability and estimating performance of the proposed scheme. Simulation results on a two DOF robot manipulator are presented to show the efficiency of the proposed neural network based observer.

AB - In this paper, a new neural network based observer is proposed for a class of nonlinear systems. The proposed observer can applied to estimate nonlinear systems with a high nonlinearity without any prior knowledge about system. This features help the proposed neuro-observer for real implementation and to use it in practice. The Lyapunov's direct method employed to show the stability and estimating performance of the proposed scheme. Simulation results on a two DOF robot manipulator are presented to show the efficiency of the proposed neural network based observer.

KW - Lyapunov stability

KW - Neural Network

KW - neuro-observer

KW - robot manipulator

KW - state observer

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M3 - Conference contribution

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BT - International Conference on Robotics and Mechatronics, ICROM 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd RSI/ISM International Conference on Robotics and Mechatronics, ICROM 2015

Y2 - 7 October 2015 through 9 October 2015

ER -

A new adaptive neural network based observer for robotic manipulators

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