DocumentCode :
3587025
Title :
The convergence of stochastic gradient iterative modal identification algorithm and application in modal analysis for space large manipulator
Author :
Panfeng Huang ; Zhenyu Lu
Author_Institution :
Res. Center of Intell. Robot., Nat. Key Lab. of Aerosp. Flight Dynamics, China
fYear :
2014
Firstpage :
2000
Lastpage :
2005
Abstract :
Nowadays the light constructors are widely used in the space large manipulators, and some properties of this kind of structure, such as low-frequency, large-range and durable vibration, have raise great attentions in aerospace area. In the paper we applied the wireless sensors networks (WSN) into the modal analysis of manipulators and proposed an interactive modal parameters identification method - SGIMID algorithm. This algorithm uses the stochastic gradient vector to improve interactive modal parameters identification (IMID) method, while the packet transmission mode between the modals is same to IMID algorithm. For the completeness of the proposed algorithm, we present the convergence proof of SGIMIDM. At last, we make applied SGIMID algorithm into the stiffness and frequencies coefficients identification of multi-DOF space manipulators. The experiment results show that, compared with IMID algorithm, the sensor nodes in SGIMID algorithm converge to the synchronous identified result with faster computing speed and less calculating burden.
Keywords :
aerospace robotics; gradient methods; manipulators; stochastic systems; vibration control; wireless sensor networks; SGIMID algorithm; WSN; aerospace area; computing speed; durable vibration; frequencies coefficients identification; interactive modal parameters identification method; light constructors; modal analysis; multiDOF space manipulators; space large manipulator; stochastic gradient iterative modal identification algorithm; stochastic gradient vector; wireless sensors networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
Type :
conf
DOI :
10.1109/ROBIO.2014.7090630
Filename :
7090630
Link To Document :
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