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Volumn 3, Issue , 2005, Pages 1854-1857

Adaptive PID control strategy based on RBF neural network identification

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; LEARNING SYSTEMS; NEURAL NETWORKS; PATTERN RECOGNITION; ROBUSTNESS (CONTROL SYSTEMS); TIME VARYING SYSTEMS; TWO TERM CONTROL SYSTEMS;

EID: 33847147558     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (23)

References (13)
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    • (1993) IFAC J. Contr. Eng. Practice , vol.1 , Issue.4 , pp. 699-714
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  • 2
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    • Applying neural network to on-line updated PID controllers for nonlinear process control
    • Junghui Chen, Tien-Chih Huang.Applying neural network to on-line updated PID controllers for nonlinear process control. Journal of Process Control, No.14 (2004), P211-230.
    • (2004) Journal of Process Control , Issue.14
    • Chen, J.1    Huang, T.2
  • 3
    • 0036055629 scopus 로고    scopus 로고
    • Ching-hung Lee,Yi-Hshiung Lee.A Novel robust PID controller design by fuzzy neural network. Proceedings of the American Control conference.May 8-10,2002, pp1561-1566.
    • Ching-hung Lee,Yi-Hshiung Lee.A Novel robust PID controller design by fuzzy neural network. Proceedings of the American Control conference.May 8-10,2002, pp1561-1566.
  • 4
    • 0034272428 scopus 로고    scopus 로고
    • Application of radial basis function network for solar-array modeling and maximum power-point prediction, IEE Pro.Gener
    • A. Ai-Amoudi, L. Zhang, Application of radial basis function network for solar-array modeling and maximum power-point prediction, IEE Pro.Gener. Transm. Distrib. 147 (2000) 310-316.
    • (2000) Transm. Distrib , vol.147 , pp. 310-316
    • Ai-Amoudi, A.1    Zhang, L.2
  • 5
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    • Numerical analyses of the internal conditions of a molten carbonate fuel cell stack: Comparison of stack performances for various gas flow types
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    • (1998) J. Power Sources , vol.71 , pp. 328-336
    • Toshiba, F.1    Ono, N.2
  • 6
    • 0033732354 scopus 로고    scopus 로고
    • Selecting radial basis function network centers with recursive orthogonal least squares training
    • J.B. Gomm, D.L. Yu, Selecting radial basis function network centers with recursive orthogonal least squares training, IEEE Trans. Neural Network 11 (2) (2000) 306-314.
    • (2000) IEEE Trans. Neural Network , vol.11 , Issue.2 , pp. 306-314
    • Gomm, J.B.1    Yu, D.L.2
  • 7
    • 0037379825 scopus 로고    scopus 로고
    • A fast training algorithm for RBF network based on subtractive clustering
    • April
    • Haralambos Sarimveis, Alex Alexandridis. A fast training algorithm for RBF network based on subtractive clustering. IEEE Trans Neural Networks, Volume: 51, April, 2003, pp. 501-505.
    • (2003) IEEE Trans Neural Networks , vol.51 , pp. 501-505
    • Sarimveis, H.1    Alexandridis, A.2
  • 8
    • 0037508527 scopus 로고    scopus 로고
    • Application of Bayesian trained RBF network to nonlinear time-series modeling
    • July
    • Rank,Erhard. Application of Bayesian trained RBF network to nonlinear time-series modeling. IEEE Trans Neural Networks, Volume: 83, Issue: 7, July, 2003, pp. 1393-1410.
    • (2003) IEEE Trans Neural Networks , vol.83 , Issue.7 , pp. 1393-1410
    • Rank, E.1
  • 9
    • 0028465208 scopus 로고
    • Radial basis unction neural network for approximation and estimation of nonlinear stochastic dynamic systems
    • Apr
    • Suni V. T. Elanayar, Yung C. Shin, Radial basis unction neural network for approximation and estimation of nonlinear stochastic dynamic systems, IEEE Transaction on Neural Network, Vol. 5,No. 4, pp.584-603, Apr.1994.
    • (1994) IEEE Transaction on Neural Network , vol.5 , Issue.4 , pp. 584-603
    • Elanayar, S.V.T.1    Shin, Y.C.2
  • 10
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    • Multi-variable functional interpolation and adaptive networks
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  • 13
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    • An introduction to radial basis functions for system identification: A comparison with other neural network methods
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    • Warwick, K.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.