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Proceedings Paper

Artificial neural network for piezoelectric control systems
Author(s): Jamil M. Bakhashwain; J. Refaee; Mehmet Sunar; M. Mohandes
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Paper Abstract

This paper presents a neural network controller for a piezoelectric controlled structure by emulating the control performance of a Linear Quadratic Gaussian (LQG) controller. The configuration of the Artificial Neural Network (ANN) is simple, yet it is efficient in terms of its high learning speed and good generalization ability. A case study is presented to demonstrate the performance of the ANN controller versus the LQG controller. The test results for different disturbances on the structure show excellent agreement between the ANN and LQG controllers.

Paper Details

Date Published: 4 June 1999
PDF: 9 pages
Proc. SPIE 3667, Smart Structures and Materials 1999: Mathematics and Control in Smart Structures, (4 June 1999); doi: 10.1117/12.350118
Show Author Affiliations
Jamil M. Bakhashwain, King Fahd Univ. of Petroleum and Minerals (Saudi Arabia)
J. Refaee, Saudi Aram Co. (Saudi Arabia)
Mehmet Sunar, King Fahd Univ. of Petroleum and Minerals (Saudi Arabia)
M. Mohandes, King Fahd Univ. of Petroleum and Minerals (Saudi Arabia)


Published in SPIE Proceedings Vol. 3667:
Smart Structures and Materials 1999: Mathematics and Control in Smart Structures
Vasundara V. Varadan, Editor(s)

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