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Titolo:
Fuzzy-sliding mode control of a polishing robot based on genetic algorithm
Autore:
Go, SJ; Lee, MC; Park, MK;
Indirizzi:
Pusan Natl Univ, Sch Mech Engn, Keumjung Ku, Pusan 609735, South Korea Pusan Natl Univ Pusan South Korea 609735 g Ku, Pusan 609735, South Korea Pusan Natl Univ, Grad Sch Mech & Intelligent Syst Engn, Pusan 609735, South Korea Pusan Natl Univ Pusan South Korea 609735 Engn, Pusan 609735, South Korea
Titolo Testata:
KSME INTERNATIONAL JOURNAL
fascicolo: 5, volume: 15, anno: 2001,
pagine: 580 - 591
SICI:
1226-4865(200105)15:5<580:FMCOAP>2.0.ZU;2-G
Fonte:
ISI
Lingua:
ENG
Soggetto:
SYSTEMS; DESIGN;
Keywords:
self tuning fuzzy inference method; genetic algorithm; fuzzy-sliding mode control; gradient descent method; Akaike's information criterion; polishing robot;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
25
Recensione:
Indirizzi per estratti:
Indirizzo: Lee, MC Pusan Natl Univ, Sch Mech Engn, Keumjung Ku, 30 Jangjeon Dong, Pusan 609735, South Korea Pusan Natl Univ 30 Jangjeon Dong Pusan South Korea 609735 h Korea
Citazione:
S.J. Go et al., "Fuzzy-sliding mode control of a polishing robot based on genetic algorithm", KSME INT J, 15(5), 2001, pp. 580-591

Abstract

This paper proposes a fuzzy-sliding mode control which is designed by a self tuning fuzzy inference method based on a genetic algorithm, Using the method, the number of inference rules and the shape of the membership functions of the proposed fuzzy-sliding muds control are optimized without the aidof an expert in robotics, The fuzzy outputs of the consequent part are updated by the gradient descent method. It is further guaranteed that the selected solution becomes the global optimal solution by optimizing Akaike's information criterion expressing the quality of the inference rules, In orderto evaluate the learning performance of the proposed fuzzy-sliding mode control based on a genetic algorithm, a trajectory tracking simulation of thepolishing robot is carried out. Simulation results show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the trajectory control result is similar to the result of the fuzzy-sliding mode control which is selected through trial error by an expert. Therefore, a designer who does not have expert knowledge of robot systems can design the fuzzy sliding mode controller using the proposed self tuning fuzzy inference method based on the genetic algorithm.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 06/07/20 alle ore 09:01:29