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A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator. / West, Craig; Montazeri, Allahyar; Monk, Stephen David et al.
In: IFAC-PapersOnLine, Vol. 49, No. 12, 2016, p. 1261-1266.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

West, C, Montazeri, A, Monk, SD & Taylor, CJ 2016, 'A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator', IFAC-PapersOnLine, vol. 49, no. 12, pp. 1261-1266. https://doi.org/10.1016/j.ifacol.2016.07.688

APA

West, C., Montazeri, A., Monk, S. D., & Taylor, C. J. (2016). A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator. IFAC-PapersOnLine, 49(12), 1261-1266. https://doi.org/10.1016/j.ifacol.2016.07.688

Vancouver

West C, Montazeri A, Monk SD, Taylor CJ. A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator. IFAC-PapersOnLine. 2016;49(12):1261-1266. Epub 2016 Aug 11. doi: 10.1016/j.ifacol.2016.07.688

Author

West, Craig ; Montazeri, Allahyar ; Monk, Stephen David et al. / A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator. In: IFAC-PapersOnLine. 2016 ; Vol. 49, No. 12. pp. 1261-1266.

Bibtex

@article{fd26dba3d0d743a1a82f80714a9e1dda,
title = "A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator",
abstract = "In this paper the problem of dynamic modeling and parameter estimation of a seven degree of freedom hydraulic manipulator is investigated. The numerical model is developed in Simulink using Sim Mechanic and Simscape toolboxes with unknown/uncertain parameters. The aim of this paper is to develop a mechanism that enables us to find a feasible set of parameters for the robot that is consistent with measurements of the input, output, and states of the system under noisy and unknown operating conditions. As the first step a genetic algorithm is developed to solve an output error system identification problem for a specific joint, i.e. joint 2, such that the parameters of the joint converge to the desired set of parameters within an acceptable accuracy. The results can be straightforwardly extended to all joints of the manipulator.",
keywords = "Parameter estimation, System identification, Nonlinear model, Genetic algorithm, Mathematical modeling",
author = "Craig West and Allahyar Montazeri and Monk, {Stephen David} and Taylor, {Charles James}",
year = "2016",
doi = "10.1016/j.ifacol.2016.07.688",
language = "English",
volume = "49",
pages = "1261--1266",
journal = "IFAC-PapersOnLine",
publisher = "IFAC Secretariat",
number = "12",
note = "8th IFAC Conference on Manufacturing Modelling, Management and Control ; Conference date: 28-06-2016",

}

RIS

TY - JOUR

T1 - A genetic algorithm approach for parameter optimization of a 7DOF robotic manipulator

AU - West, Craig

AU - Montazeri, Allahyar

AU - Monk, Stephen David

AU - Taylor, Charles James

PY - 2016

Y1 - 2016

N2 - In this paper the problem of dynamic modeling and parameter estimation of a seven degree of freedom hydraulic manipulator is investigated. The numerical model is developed in Simulink using Sim Mechanic and Simscape toolboxes with unknown/uncertain parameters. The aim of this paper is to develop a mechanism that enables us to find a feasible set of parameters for the robot that is consistent with measurements of the input, output, and states of the system under noisy and unknown operating conditions. As the first step a genetic algorithm is developed to solve an output error system identification problem for a specific joint, i.e. joint 2, such that the parameters of the joint converge to the desired set of parameters within an acceptable accuracy. The results can be straightforwardly extended to all joints of the manipulator.

AB - In this paper the problem of dynamic modeling and parameter estimation of a seven degree of freedom hydraulic manipulator is investigated. The numerical model is developed in Simulink using Sim Mechanic and Simscape toolboxes with unknown/uncertain parameters. The aim of this paper is to develop a mechanism that enables us to find a feasible set of parameters for the robot that is consistent with measurements of the input, output, and states of the system under noisy and unknown operating conditions. As the first step a genetic algorithm is developed to solve an output error system identification problem for a specific joint, i.e. joint 2, such that the parameters of the joint converge to the desired set of parameters within an acceptable accuracy. The results can be straightforwardly extended to all joints of the manipulator.

KW - Parameter estimation

KW - System identification

KW - Nonlinear model

KW - Genetic algorithm

KW - Mathematical modeling

U2 - 10.1016/j.ifacol.2016.07.688

DO - 10.1016/j.ifacol.2016.07.688

M3 - Journal article

VL - 49

SP - 1261

EP - 1266

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

IS - 12

T2 - 8th IFAC Conference on Manufacturing Modelling, Management and Control

Y2 - 28 June 2016

ER -