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Volumn , Issue , 2005, Pages 177-217

Gaussian process approaches to nonlinear modelling for control

Author keywords

Black box modelling techniques; Fuzzy models; Gaussian process approaches; Gaussian processes; Local model identification; Local model network; Modelling; Neural networks; Nonlinear control systems; Nonlinear modelling; Nonlinear systems; Nonparametric probabilistic models; Off equilibrium dynamics; Probability

Indexed keywords

FUZZY INFERENCE; FUZZY NEURAL NETWORKS; GAUSSIAN NOISE (ELECTRONIC); IDENTIFICATION (CONTROL SYSTEMS); MODELS; NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS; NONLINEAR SYSTEMS; PROBABILITY; TRANSPARENCY;

EID: 85014137088     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1049/PBCE070E_ch6     Document Type: Chapter
Times cited : (11)

References (55)
  • 1
    • 0025399567 scopus 로고
    • Identification and control of dynamical systems using neural networks
    • NARENDRA, K. S., and PARTHASARATHY, K.: ‘Identification and control of dynamical systems using neural networks’, IEEE Transactions on Neural Networks, 1990, 1 (1), pp. 4-27
    • (1990) IEEE Transactions on Neural Networks , vol.1 , Issue.1 , pp. 4-27
    • Narendra, K.S.1    Parthasarathy, K.2
  • 2
    • 0021892282 scopus 로고
    • Fuzzy identification of systems and its applications to modeling and control
    • TAKAGI, T., and SUGENO, M.: ‘Fuzzy identification of systems and its applications to modeling and control’, IEEE Transactions on Systems, Man and Cybernetics SMC, 1985, 15 (1), pp. 116-32
    • (1985) IEEE Transactions on Systems, Man and Cybernetics SMC , vol.15 , Issue.1 , pp. 116-132
    • Takagi, T.1    Sugeno, M.2
  • 6
    • 0002978835 scopus 로고
    • Curve fitting and optimal design for prediction (with discussion)
    • O’HAGAN, A.: ‘Curve fitting and optimal design for prediction (with discussion)’, Journal of the Royal Statistical Society B, 1978, 40 (1), pp. 1-42
    • (1978) Journal of the Royal Statistical Society B , vol.40 , Issue.1 , pp. 1-42
    • O’hagan, A.1
  • 9
    • 0003017575 scopus 로고    scopus 로고
    • Prediction with Gaussian processes: From linear regression to linear prediction and beyond
    • JORDAN, M. I. (Ed.), Kluwer Academic Press, Dordrecht
    • WILLIAMS, C. K. I.: ‘Prediction with Gaussian processes: from linear regression to linear prediction and beyond’, in JORDAN, M. I. (Ed.): ‘Learning and inference in graphical models’ (Kluwer Academic Press, Dordrecht, 1998)
    • (1998) Learning and inference in graphical models
    • Williams, C.K.I.1
  • 14
    • 4344584449 scopus 로고    scopus 로고
    • Occam’s razor
    • LEEN, T., DIETTERICH, T. G., and TRESP, V. (Eds), MIT Press, Cambridge, MA
    • RASMUSSEN, C. E., and GHAHRAMANI, Z.: ‘Occam’s razor’, in LEEN, T., DIETTERICH, T. G., and TRESP, V. (Eds): ‘Advances in neural information processing systems 13’ (MIT Press, Cambridge, MA, 2001) pp. 294-300
    • (2001) Advances in neural information processing systems 13 , pp. 294-300
    • Rasmussen, C.E.1    Ghahramani, Z.2
  • 15
    • 0030109138 scopus 로고    scopus 로고
    • Identification of non-linear systems using empirical data and prior knowledge - an optimization approach
    • JOHANSEN, T. A.: ‘Identification of non-linear systems using empirical data and prior knowledge - an optimization approach’, Automatica, 1996, 32, pp. 337-56
    • (1996) Automatica , vol.32 , pp. 337-356
    • Johansen, T.A.1
  • 16
    • 0031084233 scopus 로고    scopus 로고
    • On tikhonov regularization, bias and variance in nonlinear system identification
    • JOHANSEN, T. A.: ‘On tikhonov regularization, bias and variance in nonlinear system identification’, Automatica, 1997, 33, pp. 441-6
    • (1997) Automatica , vol.33 , pp. 441-446
    • Johansen, T.A.1
  • 17
    • 28044467657 scopus 로고    scopus 로고
    • Bayesian regression and classification
    • SUYKENS, J., HORVATH, G., BASU, S., MICCHELLI, C., and VANDEWALLE, J. (Eds), IOS Press, NATO Science Series III: Computer and Systems Sciences
    • BISHOP, C. M., and TIPPING, M. E.: ‘Bayesian regression and classification’, in SUYKENS, J., HORVATH, G., BASU, S., MICCHELLI, C., and VANDEWALLE, J. (Eds): ‘Advances in learning theory: methods, models and applications’, vol. 190 (IOS Press, NATO Science Series III: Computer and Systems Sciences, 2003) pp. 267-85
    • (2003) Advances in learning theory: Methods, models and applications , vol.190 , pp. 267-285
    • Bishop, C.M.1    Tipping, M.E.2
  • 20
    • 85072768928 scopus 로고    scopus 로고
    • Gaussian processes for regression
    • HASSELMO TOURETZKY, M. E., and MOZER, M. C. (Eds), MIT Press, Cambridge, MA
    • WILLIAMS, C. K. I., and RASMUSSEN, C. E.: ‘Gaussian processes for regression’, in HASSELMO TOURETZKY, M. E., and MOZER, M. C. (Eds):‘Advances in neural information processing systems 8’ (MIT Press, Cambridge, MA, 1996) pp. 514-20
    • (1996) Advances in neural information processing systems 8 , pp. 514-520
    • Williams, C.K.I.1    Rasmussen, C.E.2
  • 22
    • 32844462233 scopus 로고    scopus 로고
    • A review paper in the proceedings of an Erice summer school
    • MACKAY, D. J. C.: ‘Introduction to Monte Carlo methods’. A review paper in the proceedings of an Erice summer school, 1999
    • (1999) Introduction to Monte Carlo methods
    • Mackay, D.J.C.1
  • 23
    • 0000597408 scopus 로고    scopus 로고
    • Comparison of approximate methods for handling hyperparameters
    • MACKAY, D. J. C.: ‘Comparison of approximate methods for handling hyperparameters’, Neural Computation, 1999, 11 (5), pp. 1035-68
    • (1999) Neural Computation , vol.11 , Issue.5 , pp. 1035-1068
    • Mackay, D.J.C.1
  • 29
    • 0026899193 scopus 로고
    • Using radial basis function to approximate a function and its error bounds
    • LEONARD, J. A., KRAMER, M. A., and UNGAR, L. H.: ‘Using radial basis function to approximate a function and its error bounds’, IEEE Transactions on Neural Networks, 1992, 3 (4), pp. 624-7
    • (1992) IEEE Transactions on Neural Networks , vol.3 , Issue.4 , pp. 624-627
    • Leonard, J.A.1    Kramer, M.A.2    Ungar, L.H.3
  • 36
    • 21244470876 scopus 로고    scopus 로고
    • A comparison of multiple model and pole-placement self-tuning for the control of highly nonlinear processes
    • FAGAN, A., and FEELY, O. (Eds), Dublin, Ireland
    • GREGORČIČ, G., and LIGHTBODY, G.: ‘A comparison of multiple model and pole-placement self-tuning for the control of highly nonlinear processes’, in FAGAN, A., and FEELY, O. (Eds): Proceedings of the Irish Signals and Systems Conference, Dublin, Ireland, 2000, pp. 303-11
    • (2000) Proceedings of the Irish Signals and Systems Conference , pp. 303-311
    • Gregorčič, G.1    Lightbody, G.2
  • 40
    • 11144332281 scopus 로고    scopus 로고
    • Multiple-step ahead prediction for non linear dynamic systems - a Gaussian process treatment wih propagation of the uncertainty
    • BECKER, S., THRUN, S., and OBERMAYER, K. (Eds), MIT Press, Cambridge, MA
    • GIRARD, A., RASMUSSEN, C., QUINONERO CANDELA, J., and MURRAY-SMITH, R.: ‘Multiple-step ahead prediction for non linear dynamic systems - a Gaussian process treatment wih propagation of the uncertainty’, in BECKER, S., THRUN, S., and OBERMAYER, K. (Eds): ‘Advances in neural information processing systems’ (MIT Press, Cambridge, MA, 2002) pp. 545-52
    • (2002) Advances in neural information processing systems , pp. 545-552
    • Girard, A.1    Rasmussen, C.2    Quinonero Candela, J.3    Murray-Smith, R.4
  • 42
    • 0027007477 scopus 로고
    • Non-linear internal model control strategy for neural network models
    • NAHAS, E. P., HENSON, M. A., and SEBORG, D. E.: ‘Non-linear internal model control strategy for neural network models’, Computers and Chemical Engineering, 1992, 16, pp. 1039-57
    • (1992) Computers and Chemical Engineering , vol.16 , pp. 1039-1057
    • Nahas, E.P.1    Henson, M.A.2    Seborg, D.E.3
  • 43
    • 85024429815 scopus 로고
    • A new approach to linear filtering and prediction problems
    • Series D
    • KALMAN, R. E.: ‘A new approach to linear filtering and prediction problems’, Transactions of the ASME - Journal of Basic Engineering, 1960, 82 (Series D), pp. 35-45
    • (1960) Transactions of the ASME - Journal of Basic Engineering , vol.82 , pp. 35-45
    • Kalman, R.E.1
  • 44
    • 0002711502 scopus 로고    scopus 로고
    • Optimal reduced rank modeling, prediction, monitoring, and control using canonical variate analysis
    • Banff, Canada
    • LARIMORE, W. E.: ‘Optimal reduced rank modeling, prediction, monitoring, and control using canonical variate analysis’. IFAC1997 international symposium on Advanced Control of Chemical Processes, Banff, Canada, 1997, pp. 61-6
    • (1997) IFAC1997 international symposium on Advanced Control of Chemical Processes , pp. 61-66
    • Larimore, W.E.1
  • 45
    • 84867960650 scopus 로고    scopus 로고
    • Delay embeddings of forced systems: Ii stochastic forcing
    • STARK, J., BROOMHEAD, D. S., DAVIES, M. E., and HUKE, J.: ‘Delay embeddings of forced systems: Ii stochastic forcing’, Journal of Nonlinear Science, 2003, 13 (6), pp. 519-77
    • (2003) Journal of Nonlinear Science , vol.13 , Issue.6 , pp. 519-577
    • Stark, J.1    Broomhead, D.S.2    Davies, M.E.3    Huke, J.4
  • 46
    • 0037063251 scopus 로고    scopus 로고
    • Identification of nonlinear time series via kernels
    • DODD, T. J., and HARRIS, C. J.: ‘Identification of nonlinear time series via kernels’, International Journal of System Science, 2002, 33 (9) pp. 737-50
    • (2002) International Journal of System Science , vol.33 , Issue.9 , pp. 737-750
    • Dodd, T.J.1    Harris, C.J.2
  • 47
    • 0032673331 scopus 로고    scopus 로고
    • Analytic framework for blended multiple model systems using linear local models
    • LEITH, D. J., and LEITHEAD, W. E.: ‘Analytic framework for blended multiple model systems using linear local models’, International Journal of Control, 1999, 72 (7/8), pp. 605-19
    • (1999) International Journal of Control , vol.72 , Issue.7-8 , pp. 605-619
    • Leith, D.J.1    Leithead, W.E.2
  • 48
    • 0000262562 scopus 로고
    • Hierarchical mixtures of experts and the EM algorithm
    • JORDAN, M. I., and JACOBS, R. A.: ‘Hierarchical mixtures of experts and the EM algorithm’, Neural Computation, 1994, 6, pp. 181-214
    • (1994) Neural Computation , vol.6 , pp. 181-214
    • Jordan, M.I.1    Jacobs, R.A.2
  • 50
    • 85156191859 scopus 로고    scopus 로고
    • Bayesian methods for mixtures of experts
    • TOURETZKY, D. S., MOZER, M. C., and HASSELMO, M. E. (Eds), The MIT Press, Cambridge, MA
    • WATERHOUSE, S., MACKAY, D., and ROBINSON, T.: ‘Bayesian methods for mixtures of experts’, in TOURETZKY, D. S., MOZER, M. C., and HASSELMO, M. E. (Eds): ‘Advances in neural information processing systems’, vol. 8 (The MIT Press, Cambridge, MA, 1996) pp. 351-7
    • (1996) Advances in neural information processing systems , vol.8 , pp. 351-357
    • Waterhouse, S.1    Mackay, D.2    Robinson, T.3
  • 52
    • 0004113976 scopus 로고
    • Technical report NCRG/94/004, Neural Computing Research Group, Aston University
    • BISHOP, C. M.: ‘Mixture density networks’. Technical report NCRG/94/004, Neural Computing Research Group, Aston University, 1994
    • (1994) Mixture density networks
    • Bishop, C.M.1
  • 53
    • 4444269985 scopus 로고    scopus 로고
    • The Bayesian paradigm:Second generation neural computing
    • LISBOA, P. (Ed.), Springer-Verlag, Heidelberg
    • PENNY, W. D., HUSMEIER, D., and ROBERTS, S. J.: ‘The Bayesian paradigm:second generation neural computing’, in LISBOA, P. (Ed.): ‘Artificial neural networks in biomedicine’ (Springer-Verlag, Heidelberg, 1999)
    • (1999) Artificial neural networks in biomedicine
    • Penny, W.D.1    Husmeier, D.2    Roberts, S.J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.