Parameter Optimization of Cartesian Serial-Parallel Manipulator with Redundant Actuation Based on BP Neural Networks

Design the redundant driving structure based on a new type of universal Cartesian serial-parallel manipulator, structural parameters are optimized through objective function, relative workspace and accuracy of motion included as the main index, four BP neural networks are constructed with reiterativ...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 602-605; no. Advanced Manufacturing and Information Engineering, Intelligent Instrumentation and Industry Development; pp. 908 - 911
Main Authors Luo, Jian Guo, He, Mao Yan
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 11.08.2014
Subjects
Cartesian
Manipulators
Mathematical analysis
Mathematical models
Neural networks
Optimization
Parameters
Redundant
Serial-Parallel
Parameter
Redundant Driving
Neural Network (NN)
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Summary:Design the redundant driving structure based on a new type of universal Cartesian serial-parallel manipulator, structural parameters are optimized through objective function, relative workspace and accuracy of motion included as the main index, four BP neural networks are constructed with reiterative exercise carried out, transferred function and input parameters through the constructed and exercised neural networks, analysis and approach computation completed with pretty optimal data suggested.
Bibliography:Selected, peer reviewed papers from the 2014 2nd International Conference on Precision Mechanical Instruments and Measurement Technology (ICPMIMT 2014), May 30-31, 2014, Chongqing, China
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ISBN:9783038351948
3038351946
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.602-605.908