Improved switching for multiple model adaptive controller in noisy environment

Journal of Process Control

Volumn 22, Issue 2, 2012, Pages 390-396

  Bashivan, Pouya ^a   Fatehi, Alireza ^a  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Adaptive control; Multiple model control; Noise reduction control; Stability; Switching control

Indexed keywords

ADAPTIVE CONTROL; ADAPTIVE CONTROLLERS; HYSTERESIS FUNCTION; MEASUREMENT NOISE; MULTIPLE MODELS; NOISE REDUCTIONS; NOISY ENVIRONMENT; NON-LINEAR MODEL; PERFORMANCE FUNCTIONS; SIMULATION STUDIES; SWITCHING CONTROL; SWITCHING MECHANISM;

ADAPTIVE CONTROL SYSTEMS; CONVERGENCE OF NUMERICAL METHODS; NOISE ABATEMENT; SWITCHING;

COMPUTER SIMULATION;

EID: 84857193110     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2011.12.010     Document Type: Article

References (23)

1. K.J. Astrom, and B. Wittenmark Adaptive Control 2nd edition 1994 Prentice Hall
2. P. Bashivan, and A. Fatehi Design of multiple model controller using SOM neural network ISICE Journal of Control 3 2 2009
3. P. Bashivan, A. Fatehi, and E. Peymani Multiple-model control of pH neutralization plant using the SOM neural networks Proceedings of IEEE Conference on Control, Communication and Automation (INDICON) KA, India 2008 115 119
4. J.M. Boling, D.E. Seborg, and J.P. Hespanha Multi-model adaptive control of a simulated pH neutralization process Control Engineering Practice 15 2007 663 672 (Pubitemid 46336799)
5. B. Chadouri, R. Majumder, and B.C. Pal Application of multiple-model adaptive control strategy for robust damping of interarea oscillations in power systems IEEE Transactions on Control Systems Technology 12 2004 727 736
6. J. Cho, J.C. Principe, D. Erdogmus, and M.A. Motter Quasi-sliding mode control strategy based on multiple-linear models Neurocomputing 70 2007 960 974 (Pubitemid 46043955)
7. D. Dougherty, and D. Cooper A practical multiple model adaptive strategy for single-loop MPC Control Engineering Practice 11 2003 141 159 (Pubitemid 36225455)
8. C. Englund, and A. Verikas Ink flow control by multiple models in an offset lithographic printing process Computers & Industrial Engineering 55 2008 592 605
9. A. Fatehi, and K. Abe Flexible structure multiple modeling using irregular self-organizing maps neural network International Journal of Neural Systems 18 3 2008 233 256
10. O. Galan, J.A. Romagnoli, and A. Palazoglu Real-time implementation of multi-linear model-based control strategies - an application to a bench-scale pH neutralization reactor Journal of Process Control 14 2004 571 579
11. M.A. Henson, and D.E. Seborg Adaptive nonlinear control of a pH neutralization process IEEE Transactions on Control Systems Technology 2 August (3) 1994 169 182
12. T. Hugglund, and K.J. Astrom Supervision of adaptive algorithms Automatica 36 8 2000
13. K.S. Narendra, and J. Balakrishnan Adaptive control using multiple models IEEE Transactions on Automatic Control 42 February (2) 1997 171 187 (Pubitemid 127760579)
14. K.S. Narendra, J. Balakrishnan, and M. Kemal Ciliz Adaptation and learning using multiple models, switching, and tuning IEEE Control Systems Magazine (NY) June 1995 37 51
15. K.S Narendra, and C. Xiang Adaptive control of discrete-time systems using multiple models IEEE Transactions on Automatic Control 45 September (9) 2000 1669 1686 (Pubitemid 32067053)
16. E. Peymani, A. Fatehi, and A.K. Sedigh Automatic learning in multiple model adaptive control International Conference on Control, UKACC Manchester, UK, September 2008
17. E. Peymani, A. Fatehi, P. Bashivan, and A. Khaki Sedigh An experimental comparison of adaptive controllers on a pH neutralization pilot plant Proceedings of IEEE Conference on Control, Communication and Automation (INDICON) Kanpur, India 2008 377 382
18. J.A. Rodriguez, J.A. Romagnoli, and C.G. Goodwin Supervisory multiple regime control Journal of Process Control 13 2003 177 191 (Pubitemid 35264312)
19. A.C. Singer, G.W. Wornell, and A.V. Oppenheim Codebook prediction: a nonlinear signal modeling paradigm Proceedings of the International Conference on Acoustics, Speech, and Signal Processing CA, USA 1992 325 328
20. R.M. Smith, and T.A. Johansen Multiple Model Approaches to Modeling and Control 1997 Taylor & Francis
21. Z. Tian, and K.A. Hoo Multiple model-based control of the Tennessee-Eastman process Industrial and Engineering Chemistry Research 44 2005 3187 3202 (Pubitemid 40763448)
22. J. Walter, H. Ritter, and K. Schulten Nonlinear prediction with self-organizing maps Proceedings of the International Joint Conference on Neural Networks CA, USA 1990 589 594
23. A. Fatehi, and K. Abe Self-organizing map neural network as a multiple model identifier for time-varying systems The Sixth International Symposium on Artificial Life and Robotics (AROB 6th '01) Tokyo, January 2001 528 531