Adaptive neural network state predictor and tracking control for nonlinear time-delay systems

International Journal of Innovative Computing, Information and Control

Volumn 6, Issue 2, 2010, Pages 627-639

  Na, Jing ^a   Ren, Xuemei ^a   Gao, Yan ^a   Robert, Griñó ^b   Ramon, Costa Castelló ^b  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

Feedback control; Neural network; State predictor; Time delay system

Indexed keywords

ADAPTIVE NEURAL NETWORKS; ITERATIVE CALCULATION; LYAPUNOV CRITERION; NON-LINEARITY; NONLINEAR STATE; NONLINEAR TIME-DELAY SYSTEMS; PREDICTOR DESIGN; STABILITY ANALYSIS; STATE PREDICTOR; TIME-DELAY SYSTEMS; TRACKING CONTROLS;

DELAY CONTROL SYSTEMS; FEEDBACK; FEEDBACK CONTROL; IDENTIFICATION (CONTROL SYSTEMS); NEURAL NETWORKS; NONLINEAR SYSTEMS; STATE FEEDBACK; TIME DELAY;

ADAPTIVE CONTROL SYSTEMS;

EID: 77649308570     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (25)

1. J. P. Richard, Time-delay systems: an overview of some recent advances and open problems, Automatica, vol.39, no.10, pp.1667-1694, 2003.
2. K. Gu, V. L. Kharitonov and J. Chen, Stability of Time-Delay Systems, Birkhauser, Boston, 2003.
3. Y. Q. Xia and Y. M. Jia, Robust sliding-mode control for uncertain time-delay systems: an LMI approach, IEEE Trans. Automat. Contr., vol.48, no.6, pp.1086-1092, 2003.
4. Z. J. Palmor and M. Blau, An auto-tuner for Smith dead time compensator, Int. J. Contr., vol.60, no.1, pp.117-135, 1994.
5. Q. P. Hu and G. P. Rangaiah, A time delay compensation strategy for uncertain single-input single-output nonlinear processes, ACS Ind. Eng. Chem. Res., vol.38, no.11, pp.4309-4316, 1999.
6. J. E. Normey-Rico and E. F. Camacho, Control of Dead-time Process, Springer, Berlin, 2007.
7. J. Q. Huang and F. L. Lewis, Neural-network predictive control for nonlinear dynamic systems with time delay, IEEE Trans. Neural Networks, vol.14, no.2, pp.377-389, 2003.
8. J. Na, X. M. Ren and H. Huang, Time-delay positive feedback control for nonlinear time-delay systems with neural network compensation, ACTA Automat. Sin., vol.34, no.9, pp.1196-1203, 2008.
9. S. Huang, K. K. Tan and T. H. Lee, Applied Predictive Control, Springer, London, 2002.
10. G. P. Liu, Y. Q. Xia, J. Chen, D. Rees and W. S. Hu, Networked predictive control of systems with random network delays in both forward and feedback channels, IEEE Trans. Ind. Electron., vol.54, no.3, pp.1282-1297, 2007.
11. D. Wang, D. H. Zhou, Y. H. Jin and S. J. Qin, Adaptive generic model control for a class of nonlinear time-varying processes with input time delay, J. Proc. Contr., vol.14, no.5, pp. 517-531, 2004.
12. D. Wang, D. H. Zhou and Y. H. Jin, An extended nonlinear state predictor for a class of nonlinear time delay systems, Progr. Nat. Sci, vol.14, no.2, pp.145-151, 2004.
13. E. B. Kosmatopoulos, M. M. Polycarpou, M. A. Christodoulou and P. A. Ioannou, High-order neural network structures for identification of dynamical systems, IEEE Trans. Neural Networks, vol.6, no.2, pp.422-431, 1995.
14. X. M. Ren and A. B. Rad, Identification of nonlinear systems with unknown time-delay based on time-delay neural networks, IEEE Trans. Neural Networks, vol.18, no.5, pp.1536-1541, 2007.
15. S. S. Ge and C. Wang, Adaptive neural control of uncertain MIMO nolinear systems, IEEE Trans. Neural Networks, vol.15, no.3, pp.674-692, 2003.
16. S. J. Zhang and S. S. Hu, Output feedback tracking control for a class of MIMO nonlinear minimum phase systems based on RBF neural networks, International Journal of Innovative Computing, Information and Control, vol.4, no.4, pp.803-812, 2008.
17. A. Fekih, H. Xu and F. Chowdhury, Neural networks based system identification techniques for model based fault detection of nonlinear systems, International Journal of Innovative Computing, Information and Control, vol.3, no.5, pp.1073-1085, 2007.
18. Y. H. Tan and A. V. Cauwenberghe, Nonlinear one-step-ahead control using neural networks: control strategy and stability design, Automatica, vol.32, no.12, pp.1701-1706, 1996.
19. Y. H. Tan and A. V. Cauwenberghe, Neural-network-based d-step-ahead predictors for nonlinear systems with time delay, Eng. Appl. Artif. Intel., vol.12, pp.21-35, 1999.
20. C. H. Lu and C. C. Tsai, Generalized predictive control using recurrent fuzzy neural networks for industrial processes, J. Proc. Contr., vol.17, no.1, pp.83-92, 2007.
21. C. H. Lu and C. C. Tsai, Adaptive Predictive control with recurrent neural networks for industrial processes: An application to temperature control of a variable-frequency oil-cooling machine, IEEE Trans. Ind. Electron., vol.55, no.3, pp.1366-1375, 2008.
22. D. L. Yu, D. W. Yu and J. B. Gomm, Neural model adaptation and predictive of a chemical process rig, IEEE Trans. Contr. Sys. Tech., vol.14, no.5, pp.828-840, 2006.
23. X. M. Zhu, C. C. Hua and S. Wang, State feedback controller design of networked control systems with time delay in the plant, International Journal of Innovative Computing, Information and Control, vol.4, no.2, pp.283-290, 2008.
24. S. S. Ge, F. Hong and T. H. Lee, Adaptive neural network control for nonlinear time-delay systems with unknown virtual control coefficients, IEEE Trans. Syst. Man, Cybern., vol.34, no.2, pp.499-515, 2004.
25. J. Na, X. M. Ren, Q. Chen, J. P. Xu and Y. Gao, Adaptive neural network state predictor for nonlinear time-delay systems, Proc. of the 27th Chinese Contr. Conf., Kunming, China, pp.638-643, 2008.