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Advanced Control Concepts for Industrial Robots

  • P. Kopacek
  • P. Otto
  • J. Wernstedt
Conference paper
Part of the Schriftenreihe der Wissenschaftlichen Landesakademie für Niederösterreich book series (AKADNIEDERÖSTER)

Abstract

Many tasks in robot control are very nonlinear and complex. These tasks can be performed in an advantageous way by using fuzzy methods or artificial neuronal networks. In the first part of this paper the optimal design of fuzzy controllers acting as common nonlinear time discrete controllers is investigated. In the second part artificial neuronal networks in connection with several controller structures are presented. Best results are obtained by using the structure of the adaptive model based robot control system. It is shown that the fuzzy controller and the artificial neuronal networks lead to better results than conventional control concepts.

Keywords

Fuzzy Controller Control Circuit Industrial Robot Robot Control Linear Controller 
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-Verlag/Wien 1994

Authors and Affiliations

  • P. Kopacek
    • 1
  • P. Otto
    • 2
  • J. Wernstedt
    • 2
  1. 1.Institute for Handling Devices and RoboticsUniversity of TechnologyViennaAustria
  2. 2.Department for Automation and Systems EngineeringUniversity of TechnologyIlmenauFederal Republic of Germany

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