Please use this identifier to cite or link to this item: https://doi.org/10.1109/CDC.2007.4434457
Title: Neural network feedforward control for mechanical systems with external disturbances
Authors: Ren, X.
Lewis, F.L.
Ge, S.S. 
Zhang, J.
Issue Date: 2007
Source: Ren, X.,Lewis, F.L.,Ge, S.S.,Zhang, J. (2007). Neural network feedforward control for mechanical systems with external disturbances. Proceedings of the IEEE Conference on Decision and Control : 4687-4692. ScholarBank@NUS Repository. https://doi.org/10.1109/CDC.2007.4434457
Abstract: In this paper, a novel feedforward control based on accelerometer measurements is proposed for mechanical systems with external disturbances. The control scheme includes a feedback controller and a neural network feedforward compensator. The feedback controller is employed to guarantee the stability of the mechanical systems, while the neural network is used to provide the required feedforward compensation input for trajectory tracking with the help of a sensor to detect external vibrations. Dynamics knowledge of the plant, disturbances and the sensor is not required. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Simulation results show that the proposed controller performs well for a hard disk drive system and a two-link manipulator. © 2007 IEEE.
Source Title: Proceedings of the IEEE Conference on Decision and Control
URI: http://scholarbank.nus.edu.sg/handle/10635/51219
ISBN: 1424414989
ISSN: 01912216
DOI: 10.1109/CDC.2007.4434457
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