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Controlling Aircraft Dynamic Systems

  • Oscar Castillo
  • Patricia Melin
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 63)

Abstract

We describe in this chapter a hybrid method for adaptive model-based control of non-linear dynamic systems using Neural Networks, Fuzzy Logic and Fractal Theory. The new neuro-fuzzy-fractal method combines Soft Computing (SC) techniques with the concept of the fractal dimension for the domain of Non-Linear Dynamic System Control. The new method for adaptive model-based control has been implemented as a computer program to show that our neuro-fuzzy-fractal approach is a good alternative for controlling non-linear dynamic systems. It is well known that chaotic and unstable behavior may occur for non-linear systems. Normally, we will need to control this type of behavior to avoid structural problems with the system. We illustrate in this chapter our new methodology with the case of controlling aircraft dynamic systems. For this case, we use mathematical models for the simulation of aircraft dynamics during flight. The goal of constructing these models is to capture the dynamics of the aircraft, so as to have a way of controlling this dynamics to avoid dangerous behavior of the aircraft dynamic system.

Keywords

Fractal Dimension Fuzzy Logic Adaptive Control Fuzzy Rule Fuzzy Inference System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Physica-Verlag Heidelberg 2001

Authors and Affiliations

  • Oscar Castillo
    • 1
  • Patricia Melin
    • 1
  1. 1.Department of Computer ScienceTijuana Institute of TechnologyChula VistaUSA

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