Fuzzy System for Optical Position Sensing

Werner Brockmann

Fuzzy System for Optical Position Sensing

Werner Brockmann

Institute of Computer Engineering

Abstract

Most measurement applications are nothing but a functional relationship of one or more input signals to mostly one output, which is the sensory signal. Many of these functional mappings are very complicated and difficult to describe analytically, especially for sensor fusion problems. So methods are needed which are easy to handle. Fuzzy logic is a promising approach for its offers some useful characteristics. E.g., it allows to incorporate structural knowledge as well as to learn or to tune internal parameters automatically. In this paper, such a fuzzy system is introduced and used as a simple example of fusing multiple input signals. It is applied to an opto-electronic position sensor.

Original language	English
Pages	747-751
Number of pages	5
Publication status	Published - 01.01.1995
Event	Proceedings of the 1995 IEEE Instrumentation and Measurement Technology Conference - Waltham, United States Duration: 23.04.1995 → 26.04.1995 Conference number: 43336

Conference

Conference	Proceedings of the 1995 IEEE Instrumentation and Measurement Technology Conference
Country/Territory	United States
City	Waltham
Period	23.04.95 → 26.04.95

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Cite this

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title = "Fuzzy System for Optical Position Sensing",

abstract = "Most measurement applications are nothing but a functional relationship of one or more input signals to mostly one output, which is the sensory signal. Many of these functional mappings are very complicated and difficult to describe analytically, especially for sensor fusion problems. So methods are needed which are easy to handle. Fuzzy logic is a promising approach for its offers some useful characteristics. E.g., it allows to incorporate structural knowledge as well as to learn or to tune internal parameters automatically. In this paper, such a fuzzy system is introduced and used as a simple example of fusing multiple input signals. It is applied to an opto-electronic position sensor.",

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year = "1995",

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note = "Proceedings of the 1995 IEEE Instrumentation and Measurement Technology Conference ; Conference date: 23-04-1995 Through 26-04-1995",

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N1 - Conference code: 43336

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N2 - Most measurement applications are nothing but a functional relationship of one or more input signals to mostly one output, which is the sensory signal. Many of these functional mappings are very complicated and difficult to describe analytically, especially for sensor fusion problems. So methods are needed which are easy to handle. Fuzzy logic is a promising approach for its offers some useful characteristics. E.g., it allows to incorporate structural knowledge as well as to learn or to tune internal parameters automatically. In this paper, such a fuzzy system is introduced and used as a simple example of fusing multiple input signals. It is applied to an opto-electronic position sensor.

AB - Most measurement applications are nothing but a functional relationship of one or more input signals to mostly one output, which is the sensory signal. Many of these functional mappings are very complicated and difficult to describe analytically, especially for sensor fusion problems. So methods are needed which are easy to handle. Fuzzy logic is a promising approach for its offers some useful characteristics. E.g., it allows to incorporate structural knowledge as well as to learn or to tune internal parameters automatically. In this paper, such a fuzzy system is introduced and used as a simple example of fusing multiple input signals. It is applied to an opto-electronic position sensor.

UR - https://www.scopus.com/pages/publications/0029234723

M3 - Conference Papers

SP - 747

EP - 751

T2 - Proceedings of the 1995 IEEE Instrumentation and Measurement Technology Conference

Y2 - 23 April 1995 through 26 April 1995

ER -

Fuzzy System for Optical Position Sensing

Abstract

Conference

UN SDGs

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