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Self-Tuning Computed Torque Control: Part I

  • Mohammad Teshnehlab
  • Keigo Watanabe
Chapter
Part of the International Series on Microprocessor-Based and Intelligent Systems Engineering book series (ISCA, volume 19)

Abstract

There are several types of NNs that can be used in control systems as direct or indirect controllers (discussed in Chapter 2): the multi-layered feedforward, the Kohonen’s self-organizing map, the Hopfield network, the Boltzmann machine, etc.. These types of NNs are based on the biological nervous systems. The layered structure of parts of the brain, and multilayer (instead of single layer) arrangement of neurons in biological systems comprise the main idea of mimicking the biological neural system for obtaining higher capabilities in learning algorithms.

Keywords

Connection Weight Uniform Random Number Flexible Method TIming Gain Hopfield Network 
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

© Springer Science+Business Media Dordrecht 1999

Authors and Affiliations

  • Mohammad Teshnehlab
    • 1
  • Keigo Watanabe
    • 2
  1. 1.Faculty of Electrical EngineeringK.N. Toosi UniversityTehranIran
  2. 2.Department of Mechanical EngineeringSaga UniversityJapan

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