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Neural Network Based Adaptive Control of Piezoelectric Actuator with Unknown Hysteresis

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4 Author(s)
Han Yao ; Northeastern Univ., Boston ; Jun Fu ; Wen-Fang Xie ; Su, C.Y.

A multi-resolution wavelet analysis coupled with a neural network based approach is applied in the problem of fault diagnostics of industrial robots. The multi-resolution analysis implements discrete wavelet transforms with filters and decomposes the signal in various levels. The approximate and detailed coefficients of the decomposed signals are then used for training a feedforward neural network whose output determines the state (faulty or normal) of the robot. The neural network classifier was then implemented and monitored in a Matlab-Simulink environment using a state-flow model. Validation of the method was performed offline using experimental data obtained from an industrial robot manipulator used in the semi-conductor industry.

Published in:

American Control Conference, 2007. ACC '07

Date of Conference:

9-13 July 2007