Sensitivity-based self-learning fuzzy logic control for a servo system

M. Balenovic

doi:10.1109/37.687619

Sensitivity-based self-learning fuzzy logic control for a servo system

M. Balenovic

Control Systems

Research output: Contribution to journal › Article › Academic › peer-review

26 Citations (Scopus)

308 Downloads (Pure)

Abstract

Describes an experimental verification of a self-learning fuzzy logic controller (SLFLC). The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the proposed controller has been tested by experiment in the position control loop of a chopper fed DC servo system in the presence of a gravity-dependent shaft load and fairly high static friction. The experimental results prove that the SLFLC provides closed-loop behavior as desired and eliminates a steady-state position error

Original language	English
Pages (from-to)	41-51
Number of pages	11
Journal	IEEE Control Systems Magazine
Volume	18
Issue number	3
DOIs	https://doi.org/10.1109/37.687619
Publication status	Published - 1998

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title = "Sensitivity-based self-learning fuzzy logic control for a servo system",

abstract = "Describes an experimental verification of a self-learning fuzzy logic controller (SLFLC). The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the proposed controller has been tested by experiment in the position control loop of a chopper fed DC servo system in the presence of a gravity-dependent shaft load and fairly high static friction. The experimental results prove that the SLFLC provides closed-loop behavior as desired and eliminates a steady-state position error",

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AB - Describes an experimental verification of a self-learning fuzzy logic controller (SLFLC). The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the proposed controller has been tested by experiment in the position control loop of a chopper fed DC servo system in the presence of a gravity-dependent shaft load and fairly high static friction. The experimental results prove that the SLFLC provides closed-loop behavior as desired and eliminates a steady-state position error

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DO - 10.1109/37.687619

M3 - Article

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EP - 51

JO - IEEE Control Systems Magazine

JF - IEEE Control Systems Magazine

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Sensitivity-based self-learning fuzzy logic control for a servo system

Abstract

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