Neural-based fuzzy logic control for robot manipulators

Jun Tang, Katsutosi Kuribayashi, Keigo Watanabe, Zyun Goto

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

One of the simplest tracking controllers for industrial robot manipulators is the PID control. However, in practice, because it is considerably difficult to determine the PID parameters suitably, many studies have been reported on the tuning method of the PID parameters. The objective of the paper is to design a self-tuning PID controller for achieving the time-varying tracking control of a robot manipulator. We present a fuzzy neural network (FNN), which is used to automate the parameters tuning of the PID controller. Some experimental test results are also included to demonstrate the improvement in the tracking performance when the proposed method is used.

Original languageEnglish
Pages468-473
Number of pages6
Publication statusPublished - Dec 1 1998
Externally publishedYes
EventProceedings of the 1998 2nd International Conference on knowledge-Based Intelligent Electronic Systems (KES '98) - Adelaide, Aust
Duration: Apr 21 1998Apr 23 1998

Other

OtherProceedings of the 1998 2nd International Conference on knowledge-Based Intelligent Electronic Systems (KES '98)
CityAdelaide, Aust
Period4/21/984/23/98

ASJC Scopus subject areas

  • Computer Science(all)

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  • Cite this

    Tang, J., Kuribayashi, K., Watanabe, K., & Goto, Z. (1998). Neural-based fuzzy logic control for robot manipulators. 468-473. Paper presented at Proceedings of the 1998 2nd International Conference on knowledge-Based Intelligent Electronic Systems (KES '98), Adelaide, Aust, .