Identification and modeling of nonlinear dynamical systems using a novel self-organizing RBF-based approach

Automatica

Volumn 48, Issue 8, 2012, Pages 1729-1734

  Qiao, Jun Fei ^a   Han, Hong Gui ^a  

^a BEIJING UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Artificial neural networks; Forward only computation; Identification and modeling; Nonlinear models

Indexed keywords

HIDDEN NEURONS; MODEL PERFORMANCE; MUTUAL INFORMATIONS; NETWORK COMPLEXITY; NETWORK CONSTRUCTION; NEURAL NETWORK TRAINING; NEURON ACTIVITY; NON-LINEAR MODEL; NONLINEAR IDENTIFICATIONS; OPTIMIZATION ALGORITHMS; PARAMETER OPTIMIZATION; RADIAL BASIS FUNCTIONS; SELF ORGANIZING;

ALGORITHMS; NEURAL NETWORKS; NONLINEAR DYNAMICAL SYSTEMS; OPTIMIZATION; RADIAL BASIS FUNCTION NETWORKS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 84864482334     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2012.05.034     Document Type: Article

References (24)

1. M.S. Al-Batah, N.A.M. Isa, K.Z. Zamli, and K.A. Azizli Modified recursive least squares algorithm to train the hybrid multilayered perceptron (HMLP) network Applied Soft Computing 10 1 2010 236 244
2. S.R. Andersona, and V. Kadirkamanathan Modelling and identification of non-linear deterministic systems in the delta-domain Automatica 43 10 2007 1859 1868
3. C. Buzzi, L. Grippo, and M. Sciandrone Convergent decomposition techniques for training RBF neural networks Neural Computation 13 8 2001 1891 1920
4. L. Cheng, Z.G. Hou, and M. Tan Adaptive neural network tracking control for manipulators with uncertain kinematics, dynamics and actuator model Automatica 45 10 2009 2312 2318
5. Y.H. Chien, W.Y. Wang, Y.G. Leu, and T.T. Lee Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach IEEE Transactions on Systems Man and Cybernetics Part B: Cybernetics 41 2 2011 542 552
6. H.M. Feng Self-generation RBFNs using evolutional PSO learning Neurocomputing 70 1-3 2006 241 251
7. Y. Fu, and T.Y. Chai Nonlinear multivariable adaptive control using multiple models and neural networks Automatica 43 6 2007 1101 1110
8. J. Gonzalez, I. Rojas, J. Ortega, H. Pomares, F.J. Fernandez, and A.F. Diaz Multi-objective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation IEEE Transactions on Neural Networks 14 6 2003 1478 1495
9. H.G. Han, and J.F. Qiao A self-organizing fuzzy-neural network based on growing and pruning algorithm IEEE Transactions on Fuzzy Systems 18 6 2010 1129 1143
10. H.G. Han, and J.F. Qiao An efficient self-organizing RBF neural network for water quality predicting Neural Networks 24 7 2011 717 725
11. D.S. Huang, and J.X. Du A constructive hybrid structure optimization methodology for radial basis probabilistic neural networks IEEE Transactions on Neural Networks 19 11 2008 2099 2115
12. G.B. Huang, P. Saratchandran, and N. Sundararajan An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks IEEE Transaction on Systems, Man, and Cybernetics - Part B: Cybernetics 34 6 2004 2284 2292
13. G.B. Huang, P. Saratchandran, and N. Sundararajan A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation IEEE Transactions on Neural Networks 16 1 2005 57 67
14. A.S. Kamalabady, and K. Salahshoor Affine modeling of nonlinear multivariable processes using a new adaptive neural network-based approach Journal of Process Control 19 3 2009 380 393
15. K. Li, J.X. Peng, and E.W. Bai A two-stage algorithm for identification of nonlinear dynamic systems Automatica 42 7 2006 1189 1197
16. K. Li, J.X. Peng, and G.W. Irwin A fast nonlinear model identification method IEEE Transactions on Automatic Control 50 8 2005 1211 1216
17. J. Martensson, and H. Hjalmarsson How to make bias and variance errors insensitive to system and model complexity in identification IEEE Transactions on Automatic Control 56 1 2011 100 112
18. D.Q. Mayne, S.V. Rakovic, R. Findeisen, and F. Allgower Robust output feedback model predictive control of constrained linear systems: time varying case Automatica 45 9 2009 2082 2087
19. J.X. Peng, K. Li, and G.W. Irwin A novel continuous forward algorithm for RBF neural modelling IEEE Transactions on Automatic Control 52 1 2007 117 122
20. J.F. Qiao, and H.G. Han A repair algorithm for radial basis function neural network and its application to chemical oxygen demand modelling International Journal of Neural Systems 20 1 2010 63 74
21. F.G. Rossomando, C. Soria, and R. Carelli Autonomous mobile robots navigation using RBF neural compensator Control Engineering Practice 19 3 2011 215 222
22. T.B. Schon, A. Wills, and B. Ninness System identification of nonlinear state-space models Automatica 47 1 2011 39 49
23. F. Schwenker, H.A. Kestler, and G. Palm Three learning phases for radial-basis-function networks Neural Networks 14 4-5 2001 439 458
24. S. Wu, and T.W.S. Chow Self-organizing and self-evolving neurons: a new neural network for optimization IEEE Transaction on Neural Networks 18 2 2007 385 396