Self-Tuning Computed Torque Control: Part II

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


Multilayered neural networks (MNNs) have been known for more than three decades. The supervised training mode of MNNs have been developed by [1]–[3] in more specific methods such as BP learning algorithms Also, many researches have looked for more specific properties of MNNs and their training modes. However, it should be noted that the conventional MNNs need more times in the learning process. From this motivation, the ability and learning capability of the single flexible NN is further examined. That is, this chapter illustrates the replacement of the conventional MNN with the multilayered flexible NN which results in better performance


Connection Weight Input Torque Uniform Random Number Cerebellar Model Articulation Controller Multilayered Neural 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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