JRM Vol.11 No.1 pp. 60-66
doi: 10.20965/jrm.1999.p0060


Impedance Control Using Anisotropic Fuzzy Environment Models

Fusaomi Nagata*, Keigo Watanabe**, Kazuya Sato** and Kiyotaka Izumi***

*Interior Design Research Institute, Fukuoka Industrial Technology Center, Agemaki-405-3, Ohkawa, Fukuoka 831-0031, Japan

**Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, Honjomachi-1, Saga 840-8502, Japan

***Department of Mechanical Engineering, Faculty of Science and Engineering, Saga University, Honjomachi-1, Saga 840, Japan

August 26, 1998
November 19, 1998
February 20, 1999
robot, compliance, impedance control, force control, learning control, fuzzy environment models, genetic algorithms, polishing

We describe impedance control for force control in unknown environments, proposing anisotropic fuzzy environment models that estimate environmental stiffness using fuzzy reasoning and generate time-varying damping for stable force control. Each model is automatically taught with genetic algorithms (GAs), in which evaluation is made for force control in several known environments. Taught models are integrated for generalization. We apply models to tasks in which an industrial robot sands or polishes wood is differently stiff in different direction. Numerical simulations demonstrate the effectiveness of our method.

Cite this article as:
Fusaomi Nagata, Keigo Watanabe, Kazuya Sato, and Kiyotaka Izumi, “Impedance Control Using Anisotropic Fuzzy Environment Models,” J. Robot. Mechatron., Vol.11, No.1, pp. 60-66, 1999.
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Last updated on Feb. 25, 2021