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2002•Unpublished venueRequires access

Application of fuzzy logic to robotic control

H. Vashisth, Peng-Yung Woo

Open publisher page 4 citations

Abstract

This paper describes how fuzzy logic can be applied to robotic control using software tools on personal computers. First, the fundamentals of fuzzy logic and robotics are discussed. Second, fuzzy controller designs for a two-link manipulator and for robot PUMA 560 (the last three links locked) are proposed. C language code is developed to simulate the controller designs. Fuzzy Inference Development Environment (FIDE) software from Aptronix, Inc. is used for development of fuzzy if-then rules. The contribution of this paper is the exploration of nonconventional methods for control of highly nonlinear systems.

About this research paper

What this paper is about

This paper describes how fuzzy logic can be applied to robotic control using software tools on personal computers. First, the fundamentals of fuzzy logic and robotics are discussed. Second, fuzzy controller designs for a two-link manipulator and for robot PUMA 560 (the last three links locked) are proposed. C language code is developed to simulate the controller designs. Fuzzy Inference Development Environment (FIDE) software from Aptronix, Inc. is used for development of fuzzy if-then rules. The contribution of this paper is the exploration of nonconventional methods for control of highly nonlinear systems.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper describes how fuzzy logic can be applied to robotic control using software tools on personal computers. First, the fundamentals of fuzzy logic and robotics are discussed. Second, fuzzy controller designs for a two-link manipulator and for robot PUMA 560 (the last three links locked) are proposed. C language code is developed to simulate the controller designs. Fuzzy Inference Development Environment (FIDE) software from Aptronix, Inc. is used for development of fuzzy if-then rules. The contribution of this paper is the exploration of nonconventional methods for control of highly nonlinear systems.

Key concepts: Fuzzy electronics, Fuzzy logic, Control engineering, Fuzzy Control Language, Computer science, Fuzzy control system, Neuro-fuzzy, Robotics

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