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.
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© 1994 Springer-Verlag/Wien
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Kopacek, P., Otto, P., Wernstedt, J. (1994). Advanced Control Concepts for Industrial Robots. In: Kopacek, P. (eds) Robotics in Alpe-Adria Region. Schriftenreihe der Wissenschaftlichen Landesakademie für Niederösterreich. Springer, Vienna. https://doi.org/10.1007/978-3-7091-9346-4_3
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DOI: https://doi.org/10.1007/978-3-7091-9346-4_3
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82545-7
Online ISBN: 978-3-7091-9346-4
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