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Improvement of control performance for low-dimensional number of fuzzy labelings using simplified inference method

✍ Scribed by Akifumi Otsuboa; Kenichiro Hayashi; Shuta Murakami; Mikio Maeda

Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
672 KB
Volume
90
Category
Article
ISSN
0165-0114

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✦ Synopsis

The central concept of fuzzy control is fuzzy inference, and the "simpltj?ed inference method" which is aimed at increasing the speed of the fuzzy inference has recently been used to realize a high-speed fuzzy controller. Also, in designing a fuzzy controller, a high dimension such as 7 x 7 and 5 x 5 partitions is frequently used as the number of fuzzy labelings. However, as the number of fuzzy labelings becomes high-dimensional, the number of control parameters increases rapidly and the tuning of a fuzzy controller becomes difficult. Therefore, it is required that a fuzzy controller is partitioned into a low-dimensional number of fuzzy labelings such as 3 x 3 partition.

With this in mind, first, an improvement method of control performance for low-dimensional number of fuzzy labelings using the "simpli$ed inference method" with high-speed inference is proposed. Next, the effectiveness of this improvement method is examined based on several simulation results. Lastly, this improvement method is investigated using a control map which represents the nonlinear characteristics of a fuzzy controller. 0 1997 Elsevier Science B.V.

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