Neural Network Based Tracking Control of Mechanical Systems

[+] Author and Article Information
T. Efrati, H. Flashner

Department of Mechanical Engineering, University of Southern California, Los Angeles, CA 90089-1453

J. Dyn. Sys., Meas., Control 121(1), 148-154 (Mar 01, 1999) (7 pages) doi:10.1115/1.2802435 History: Received May 05, 1997; Online December 03, 2007


A method for tracking control of mechanical systems based on artificial neural networks is presented. The controller consists of a proportional plus derivative controller and a two-layer feedforward neural network. It is shown that the tracking error of the closed-loop system goes to zero while the control effort is minimized. Tuning of the neural network’s weights is formulated in terms of a constrained optimization problem. The resulting algorithm has a simple structure and requires a very modest computation effort. In addition, the neural network’s learning procedure is implemented on-line.

Copyright © 1999 by The American Society of Mechanical Engineers
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