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Volumn 31, Issue 3, 2000, Pages 401-408

Synthesis of the sliding-mode neural network controller for unknown nonlinear discrete-time systems

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; LINEAR SYSTEMS; LYAPUNOV METHODS; NONLINEAR CONTROL SYSTEMS; PROBLEM SOLVING; RECURRENT NEURAL NETWORKS; SLIDING MODE CONTROL;

EID: 0034161021     PISSN: 00207721     EISSN: None     Source Type: Journal    
DOI: 10.1080/002077200291244     Document Type: Article
Times cited : (14)

References (15)
  • 1
    • 0031997004 scopus 로고    scopus 로고
    • A recurrent neural network based real-time learning control strategy applying to nonlinear systems with unknown dynamics
    • Chow, T.W.S., and Fang, Y., 1998, A recurrent neural network based real-time learning control strategy applying to nonlinear systems with unknown dynamics. IEEE Transactions on Industrial Electronics, 45, 151-161.
    • (1998) IEEE Transactions on Industrial Electronics , vol.45 , pp. 151-161
    • Chow, T.W.S.1    Fang, Y.2
  • 2
    • 0025386981 scopus 로고
    • Sliding mode control of a discrete system
    • Furuta, K., 1990, Sliding mode control of a discrete system. Systems and Control Letters, 14, 145-152.
    • (1990) Systems and Control Letters , vol.14 , pp. 145-152
    • Furuta, K.1
  • 3
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • Hornik, K., Stichcombe, M., and White, H., 1989, Multilayer feedforward networks are universal approximators. Neural Networks, 2, 359-366.
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1    Stichcombe, M.2    White, H.3
  • 5
    • 0027699924 scopus 로고
    • Identification and decentralized adaptive control using dynamical neural networks with application to robotic manipulators
    • Karakasoglu, A., Sudharsanan, S.I., and Sundareshan, M.K., 1993, Identification and decentralized adaptive control using dynamical neural networks with application to robotic manipulators. IEEE Transactions on Neural Networks, 4, 919-930.
    • (1993) IEEE Transactions on Neural Networks , vol.4 , pp. 919-930
    • Karakasoglu, A.1    Sudharsanan, S.I.2    Sundareshan, M.K.3
  • 6
    • 0029207879 scopus 로고
    • Diagonal recurrent neural networks for dynamic systems control
    • Ku, C.C., and Lee, K.Y., 1995, Diagonal recurrent neural networks for dynamic systems control. IEEE Transactions on Neural Networks, 6, 144-156.
    • (1995) IEEE Transactions on Neural Networks , vol.6 , pp. 144-156
    • Ku, C.C.1    Lee, K.Y.2
  • 9
    • 0029375851 scopus 로고
    • Gradient calculations for dynamic recurrent neural networks: A survey
    • Pearlmutter, B.A., 1995, Gradient calculations for dynamic recurrent neural networks: a survey. IEEE Transactions on Neural Networks, 6, 1212-1228.
    • (1995) IEEE Transactions on Neural Networks , vol.6 , pp. 1212-1228
    • Pearlmutter, B.A.1
  • 11
    • 0020799551 scopus 로고
    • Tracking control of nonlinear system using sliding surfaces, with application to robot maipulators
    • Slotine, J.J., and Shastry, S., 1983, Tracking control of nonlinear system using sliding surfaces, with application to robot maipulators. International Journal of Control 38, 465-492.
    • (1983) International Journal of Control , vol.38 , pp. 465-492
    • Slotine, J.J.1    Shastry, S.2
  • 12
    • 0028392484 scopus 로고
    • Back propagation through adjoints for the identification of nonlinear dynamic systems using recurrent neural models
    • Srinivasan, B., Prasad, U.R., and Rao, N.J., 1994, Back propagation through adjoints for the identification of nonlinear dynamic systems using recurrent neural models. IEEE Transactions on Neural Networks, 5, 213-228.
    • (1994) IEEE Transactions on Neural Networks , vol.5 , pp. 213-228
    • Srinivasan, B.1    Prasad, U.R.2    Rao, N.J.3
  • 13
    • 0026838984 scopus 로고
    • Variable structure control design on discrete-time systems-another viewpoint
    • Wang, W.J., and Wu, G.H., 1992, Variable structure control design on discrete-time systems-another viewpoint. Control Theory and Advanced Technology, 8, 1-16.
    • (1992) Control Theory and Advanced Technology , vol.8 , pp. 1-16
    • Wang, W.J.1    Wu, G.H.2
  • 14
    • 0001202594 scopus 로고
    • A learning algorithm for continuously running fully recurrent neural network
    • Williams, R.J., and Zipser, D., 1989, A learning algorithm for continuously running fully recurrent neural network. Neural Computation, 1, 270-280.
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    • Williams, R.J.1    Zipser, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.