Control of nonlinear servo systems using neural networks
DOI:
https://doi.org/10.21754/tecnia.v9i1.413Keywords:
Neural networks, Identification, PID, Smart monitoring, FeedbackAbstract
In this work, the problem of trajectory identification of nonlinear systems using neural networks is presented. The theoretical results are verified by means of an experimental study in which the nonlinear system is made up of a permanent magnet DC servomotor with reduction that also has a rod coupled to the motor shaft, in the manner of a One Degree of Freedom Robotic Arm ( BRIL), where the rod is capable of moving in a plane perpendicular to the motor axis and is controlled by the armature voltage applied to the servomotor.
Downloads
References
[1] James A. Freeman/ David M. Skapura, Redes Neuronales. Algoritmos, aplicaciones y técnicas de programación. Addison Wesley Iberoamericana, S. A. 1993.
[2] Simon Haykin, Neural Networks, Macmillan College publishing Company. Inc 1994.
[3] Kumpati S. Narendra and Kannan Pathasarathy, Identification and Control of Dynamical Systems Using Neural Networks, IEEE Transactions on Neural Networks. Vol, l, March 1990.
[4] Octave, Sofware para cálculos matemáticos. University of Wisconsin-Madison, ftp://ftp.che.wise.edu/pub/octave.
[5] Astrom, K.J, and Wittenmark B., Computer Controlled Systems: Theory and Desing. Prentice Hall 2da edción, 1990.
[6] Priyadarshee D. Mathur, Servo Desing for High Speed Low-Tension Tape Transport. Carnegie Mellon University, Pittsburgh, Pennsylvania, December 1994.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 1998 TECNIA
This work is licensed under a Creative Commons Attribution 4.0 International License.