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Volumn , Issue , 2008, Pages 694-698

Adaptive PID controller based on online LSSVM identification

Author keywords

Identification; LSSVM; Nonlinear time varying system; PID

Indexed keywords

ASYMPTOTIC ANALYSIS; CURVE FITTING; ELECTRIC CONTROL EQUIPMENT; ELECTRONICS INDUSTRY; IDENTIFICATION (CONTROL SYSTEMS); LEAST SQUARES APPROXIMATIONS; MECHATRONICS; NEURAL NETWORKS; PROPORTIONAL CONTROL SYSTEMS; SUPPORT VECTOR MACHINES; THREE TERM CONTROL SYSTEMS; TIME SHARING SYSTEMS; TIME VARYING CONTROL SYSTEMS; TIME VARYING SYSTEMS; TWO TERM CONTROL SYSTEMS;

EID: 52449118749     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AIM.2008.4601744     Document Type: Conference Paper
Times cited : (25)

References (13)
  • 1
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  • 3
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    • Man Gyun, N.1
  • 5
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    • Li, C.1    Lian, J.2
  • 6
    • 45149106856 scopus 로고    scopus 로고
    • Adaptive PID Decoupling Control Based on RBF Neural Network and Its Application
    • Beijing, China, pp, November
    • M. Zhang, Z. Wang, and P. Wang, "Adaptive PID Decoupling Control Based on RBF Neural Network and Its Application," Int. Conf. on Wavelet Analysis and Pattern Recognition, Beijing, China, pp.727-731, November 2007.
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  • 7
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    • Applying neural network to on-line updated PID controllers for nonlinear process control
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    • Nonlinear Dynamic System Identification Using Least Squares Support Vector Machine Regression
    • Shanghai, China, pp, August
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.