Experimental investigation of active vibration control using a filtered-error neural network and piezoelectric actuators

Authors:
Yali Zhou;Qizhi Zhang;Xiaodong Li;Woonseng Gan
Affiliations:
Department of Computer Science and Automation, Beijing Institute of Machinery, Beijing, China;Department of Computer Science and Automation, Beijing Institute of Machinery, Beijing, China;Institute of Acoustic, Academia Sinica, People's Republic of China;School of EEE, Nanyang Technological University, Singapore
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Year:
2005

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Active Noise Control Systems: Algorithms and DSP Implementations

Active Noise Control Systems: Algorithms and DSP Implementations
Active control of vibration using a neural network

IEEE Transactions on Neural Networks

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Abstract

The filtered-error back-propagation neural network (FEBPNN) algorithm for control of smart structure is investigated experimentally. Piezoelectric actuator is employed to suppress the structural vibration. The controllers based on the FEBPNN algorithm and the filtered-x least mean square (FXLMS) algorithm are implemented on a digital signal processor (DSP) TMS320VC33. The experimental verification tests show that the FEBPNN algorithm is effective for a nonlinear control problem, and has better tracking ability under change of the primary disturbance signal.