Intelligent position/force control of robot manipulators using fuzzy-neuro

Kazuo Kiguchi, Toshio Fukuda

研究成果: ジャーナルへの寄稿学術誌査読


Hybrid position/force control is one of the most effective methods to control the position and force of robot manipulators accurately. In most research into the hybrid position/force control it is assumed that the property and shape of the environment is previously known. In this paper, we propose a fuzzy environment evaluator and the concept of a fuzzy vector which can be used to make the fuzzy-neuro position/force controller intelligent. The intelligent hybrid position/force controller can be applied in an environment whose property and shape are unknown. At first, the intelligent controller searches the force control direction using a fuzzy vector as it applied force to the environment. The controller is able to deal with noisy signal from the force sensor more efficiently using the fuzzy vector. Then the intelligent controller applies the force effectively to the environment whose properties are unknown using the fuzzy environment estimator. The effectiveness of the proposed control method is evaluated by computer simulations.

ジャーナルNippon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
出版ステータス出版済み - 1997

!!!All Science Journal Classification (ASJC) codes

  • 材料力学
  • 機械工学
  • 産業および生産工学


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