The Robot Wrist Sensor Dynamic Mode Building Method Based on Genetic Wavelet Neural Networks

A kind of new dynamic modeling method is presented based on improved genetic algorithm (IGA) and wavelet neural networks (WNN) and the principle of algorithm is introduced for a new type robot wrist force sensor. The dynamic model of the wrist force sensor is set up according to data of the dynamic...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 455; pp. 389 - 394
Main Authors Yu, A Long, Dai, Jin Qiao
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.01.2014
Subjects
Wrist Force Sensor
Dynamic Modeling
Genetic Algorithm (GA)
Wavelet Neural Networks
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Summary:A kind of new dynamic modeling method is presented based on improved genetic algorithm (IGA) and wavelet neural networks (WNN) and the principle of algorithm is introduced for a new type robot wrist force sensor. The dynamic model of the wrist force sensor is set up according to data of the dynamic calibration, where the structure and parameters of wavelet neural networks of the dynamic model are optimized by genetic algorithm. The results show that the proposed method can overcome the shortcomings of easy convergence to the local minimum points of BP algorithm, and the network complexity, the convergence and the generalization ability are well compromised and the training speed and precision of model are increased.
Bibliography:Selected, peer reviewed papers from the 2013 3rd International Conference on Mechanical Materials and Manufacturing Engineering (ICMMME 2013), October 10th, 2013, Shanghai, China
ISBN:9783037859223
3037859229
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.455.389