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Intelligent Control of Robotic 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 new method for adaptive model-based control of robotic dynamic systems using a new hybrid neuro-fuzzy-fractal approach. Intelligent control of robotic systems is a difficult problem because the dynamics of these systems is highly non-linear. We describe an intelligent system for controlling robot manipulators to illustrate our neuro-fuzzy-fractal hybrid approach for adaptive control. We use a new fuzzy inference system for reasoning with multiple differential equations for model selection based on the relevant parameters for the problem. In this case, the fractal dimension of a time series of measured values of the variables is used as a selection parameter. We use neural networks for identification and control of robotic dynamic systems.

Keywords

Fractal Dimension Fuzzy Logic Adaptive Control Robotic System Hide Neuron 
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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