Modified defuzzifier for control of the inverted pendulum using learning

Jeen Shing Wang; Robert McLaren

Modified defuzzifier for control of the inverted pendulum using learning

Jeen Shing Wang, Robert McLaren

Department of Electrical Engineering

Research output: Contribution to conference › Paper › peer-review

3 Citations (Scopus)

Abstract

This paper introduces a novel defuzzification procedure to segment the input domains and assign selectable gain factors. With proper factor values in the defuzzifier, a fuzzy logic controller can speed-up the transient response without affecting stability. In addition, an instability due to inappropriate control rules can be accommodated. Also, the proposed defuzzifier can improve the system performance by using a Genetic Algorithm to learn the gain factors.

Original language	English
Pages	118-123
Number of pages	6
Publication status	Published - 1997
Event	Proceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97 - Syracuse, NY, USA Duration: 1997 Sep 21 → 1997 Sep 24

Other

Other	Proceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97
City	Syracuse, NY, USA
Period	97-09-21 → 97-09-24

All Science Journal Classification (ASJC) codes

Computer Science(all)
Mathematics(all)

Cite this

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title = "Modified defuzzifier for control of the inverted pendulum using learning",

abstract = "This paper introduces a novel defuzzification procedure to segment the input domains and assign selectable gain factors. With proper factor values in the defuzzifier, a fuzzy logic controller can speed-up the transient response without affecting stability. In addition, an instability due to inappropriate control rules can be accommodated. Also, the proposed defuzzifier can improve the system performance by using a Genetic Algorithm to learn the gain factors.",

author = "Wang, {Jeen Shing} and Robert McLaren",

year = "1997",

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AU - Wang, Jeen Shing

AU - McLaren, Robert

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N2 - This paper introduces a novel defuzzification procedure to segment the input domains and assign selectable gain factors. With proper factor values in the defuzzifier, a fuzzy logic controller can speed-up the transient response without affecting stability. In addition, an instability due to inappropriate control rules can be accommodated. Also, the proposed defuzzifier can improve the system performance by using a Genetic Algorithm to learn the gain factors.

AB - This paper introduces a novel defuzzification procedure to segment the input domains and assign selectable gain factors. With proper factor values in the defuzzifier, a fuzzy logic controller can speed-up the transient response without affecting stability. In addition, an instability due to inappropriate control rules can be accommodated. Also, the proposed defuzzifier can improve the system performance by using a Genetic Algorithm to learn the gain factors.

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M3 - Paper

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T2 - Proceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97

Y2 - 21 September 1997 through 24 September 1997

ER -

Modified defuzzifier for control of the inverted pendulum using learning

Abstract

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All Science Journal Classification (ASJC) codes

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