Neural Networks Control of a Magnetic Levitation System

Abstract

This report results from a contract tasking Lebanese University-Faculty of Engineering, Section I as follows: The purpose of the work is a simulating investigation of the use of artificial neural networks (ANN) in conjunction of proportional-integral-derivative (PID) controllers in control of non-contacting active magnetic bearings (AMB). The objective of this technique is to reduce the effect of the unbalance on the rotor displacement without the estimating perturbation. The work consists of the following: 1) application of artificial neural networks (multi-layer perceptrons) for nonlinear model of the active magnetic bearing by using the dynamic back-propagation methods for the adjustment of parameters; and 2) application of artificial neural networks in controlling closed-loop active magnetic bearing and comparison with the use of PID controllers. The obtained results should create a basis for a further research program connecting the fundamental knowledge with practical applications.

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Document Details

Document Type
Technical Report
Publication Date
Apr 17, 2001
Accession Number
ADA392568

Entities

People

  • Chaiban Nasr

Organizations

  • Lebanese University

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Bearings
  • Cascade Structures
  • Closed Loop Systems
  • Control Systems
  • Engineering
  • Maglev
  • Magnetic Bearings
  • Mechanical Engineering
  • Neural Networks
  • Nonlinear Dynamics
  • Nonlinear Systems
  • Parallel Computing
  • Parallel Processing
  • Pattern Recognition
  • Precision

Readers

  • Neural Network Machine Learning.
  • Robotics and Automation.
  • Tribology (the study of the boundary interaction between sliding surfaces, lubrication, wear and friction).

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks