Adaptive neural model-based decentralized predictive control

International Journal of Systems Science

Volumn 31, Issue 1, 2000, Pages 119-130

  Wang, D H ^a   Soh, C B ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; COMPUTER SIMULATION; DECENTRALIZED CONTROL; MULTIVARIABLE SYSTEMS; NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS;

NONLINEAR PROCESSES;

PREDICTIVE CONTROL SYSTEMS;

EID: 0033993162     PISSN: 00207721     EISSN: None     Source Type: Journal    
DOI: 10.1080/002077200291523     Document Type: Article

References (40)

1. Astrom K.J., 1989, Toward intelligent control. IEEE Control Systems Magazine, 4, 60-64.
2. Bhat, N.V., and McAvoy, T.J., 1990, Modeling chemical process systems via neural computation. IEEE Control Systems Magzine, 10, 24-29.
3. Billins, S.A., Jamaluddin, H.B., and Chen, S., 1992, Properties of neural networks with applications to modelling nonlinear dynamical systems. International Journal of Control, 55, 193-224.
4. Chen, F.C., and Khalil, H., 1992, Adaptive control of nonlinear systems using neural networks. International Journal of Control, 55, 1299-1317.
5. Chen, F.C., and Khalil, H., 1995, Adaptive control of a class of nonlinear discrete-time systems using neural networks. IEEE Transactions on Automatic Control, 40, 791-801.
6. Chen, S., and Billings, S.A., 1992, Neural networks for nonlinear dynamic systems modelling and identification. International Journal of Control, 56, 319-346.
7. Chen, S., Billings, S.A., and Grant, P.M., 1990, Nonlinear systems identification using neural networks. International Journal of Control, 51, 1191-1214.
8. Chen, S., Cowan, C.F.N., and Billings, S.A., 1996, Parallel recursive prediction error algorithm for training layered neural networks. International Journal of Control, 51, 1215-1228.
9. Clark, D.W., Mohtadi, C., and Tuffs, P.S., 1987. Generalized predictive control, part i: The basic algorithm; part ii: extension and interpretations. Automatica, 23, 137-160.
10. Cybenko, G., 1989, Approximation by superpositions of a sigmoidal function. Math. Control Signal Systems, 2, 303-314.
11. Fukuda, T., and Shibata, T., 1992, Theory and applications of neural networks for industrial control systems. IEEE Transactions on Industrial Electronics, 39, 472-489.
12. Funahashi, K.I., 1989, On the approximate realization of continuous mappings by neural networks. Neural Networks, 2, 183-192.
13. Goodwin, G.C., and Sin, K.S., 1984, Adaptive filtering, prediction and control. (Englewood Cliffs, New Jersey: Prentice-Hall).
14. Hornik, K., Stinchcombe, M., and White, H., 1989, Multilayer feedforward networks are universal approximators. Neural Networks, 2, 359-366.
15. Hunt, K.J., and Sbarbaro, D., 1991, Neural networks for nonlinear internal model control. IEE Proceedings-D, Control Theory and Applications, 138, 431-438.
16. Hunt, K.J., Sbarbaro, D., Zbikowski, R., and Gawthrop, R.J., 1992, Neural networks for control systems-a survey. Automatica, 28, 1083-1112.
17. Khalid, M., and Omatu, S., 1990, A neural network controller for a temperature control system. IEEE Control Systems Magazine, 12, 58-64.
18. Kreisselmeier, G., and Anderson, B., 1986, Robust model reference adaptive control. IEEE Transactions on Automatic Control, 31, 127-133.
19. Lambert, J.M., and Hecht-Nielsen, R., 1991, Application of feed-forward and recurrent neural networks to chemical plant predictive modeling. Proc. of IJCNN, 1, 372-378.
20. Levin, A.U., and Narendra, K.S., 1993, Control of nonlinear dynamical systems using neural networks: controllability and stabilization. IEEE Transactions on Neural Networks, 4, 192-206.
21. Miller, W., Sutton, R., and Werbos, P., 1990, Neural networks for control (Cambridge: MA: MIT Press).
22. Mills, P.M., Zomaya, A.Y., and Tade, M.O., 1994, Adaptive model-based control using neural networks. International Journal of Control, 60, 1163-1192.
23. Narendra, K.S., and Parthasarathy, K., 1990, Identification and control of dynamical systems using neural networks. IEEE Transactions on Neural Networks, 1, 4-27.
24. Nguyen, D.H., and Widrow, B., 1991, Neural networks for self-learning control systems. International Journal of Control, 54, 1439-1451.
25. Pao, Y.H., 1989, Adaptive pattern recognition and neural networks (Reading MA: Addison-Wesley).
26. Pao, Y.H., Phillips, S.M., and Sobajic, D.J., 1922, Neural-net computing and the intelligent control of systems. International Journal of Control, 56, 263-289.
27. Rumelhart, D.E., Hinton, G.E., and Williams, R.J., 1986, Rumelhart and McClelland (eds), Learning Internal Representations by Error Propagation, Parallel Distributed Processing (Cambridge, MA: MIT Press).
28. Saint-Donat, J., Bhat, N., and Mcavoy, T.J., 1991, Neural net based model predictive control. International Journal of Control, 54, 1453-1468.
29. Sastry, P.S., Santharam, G., and Unnikrishanan, K.P., 1994, Memory neuron networks for identification and control of dynamical systems. IEEE Transactions on Neural Networks, 5, 306-319.
30. Spall, J.C., and Cristion, J.A., 1994, Nonlinear adaptive control using neural networks: Estimation based on a smoothed form of simultaneous perturbation gradient approximation. Statistica Sinica, 4, 1-27.
31. Stromborg, B.J., Toivonen, H.T., Haggblom, K.E., and Waller, K.V., 1995, Multivariable nonlinear and adaptive control of a distillation column. AIChE Journal, 41, 195-199.
32. Tanomaru, J., and Omatu S., 1992, Process control by on-line trained neural controllers. IEEE Transactions on Industrial Electronics, 39, 511-521.
33. Waller, K.V., Finnerman, D.H., Sandelin, P.M., Haggblom, K.E., and Gustafsson, S.E., 1988, An experimental comparison of four control structures for two-points control of distillation. Ind. Engng. Chem. Res., 27, 624-628.
34. Wang, D.H., 1995, A study on adaptive neural control schemes for nonlinear dynamical systems. PhD thesis, Dept. of Automatic Control, Northeastern University, P. R. China.
35. Wang, D.H., and Chai, T.Y., 1994, Multivariable nonlinear adaptive control using neural networks. Proc. of the 33rd IEEE CDC, USA, 2, 2500-2505.
36. Watanabe, K., Fukuda, T., and Tzafestas, S.G., 1991, Learning algorithms of layered neural networks via extended kalman filters. International Journal of Control, 52, 753-768.
37. Widrow, B., 1990, Adaptive inverse control. Proc. of SPIE, 1294, 12-21.
38. Willis, M.J., Montague, G.A., Di Massimo, C., Tham, M.T., and Morris, A.J., 1992, Artificial neural networks in process estimation and control. Automatica, 28, 1181-1187.
39. Willis, M.J., Di Massimo, C., Monyague, G.A., Tham, M.T., and Morris, A.J., 1991, On neural networks in chemical process control. IEE Proceedings-D, Control Theory and Applications, 138, 256-266.
40. Yabuta, T., and Yamada, T., 1992, Neural network controller characteristics with regard to adaptive control. IEEE Transactions on Systems, Man and Cybernetics, 22, 170-177.