Real-time tracking on adaptive critic design with uniformly ultimately bounded condition

IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL

Volumn , Issue , 2013, Pages 39-46

  Ni, Zhen ^a   Fang, Xiao ^a   He, Haibo ^a   Zhao, Dongbin ^b   Xu, Xin ^c  

^a University of Rhode Island   (United States)

^b INSTITUTE OF AUTOMATION   (China)

^c NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CRITIC DESIGNS; HEURISTIC DYNAMIC PROGRAMMING; NONLINEAR TRACKING CONTROLLER; REAL TIME TRACKING; STABILITY ANALYSIS; UNIFORMLY ULTIMATELY BOUNDED; VALUE FUNCTION APPROXIMATION; WEIGHTS ESTIMATION;

ARTIFICIAL INTELLIGENCE; ERRORS; REINFORCEMENT LEARNING; VIRTUAL REALITY;

DYNAMIC PROGRAMMING;

EID: 84891525568     PISSN: 23251824     EISSN: 23251867     Source Type: Conference Proceeding    
DOI: 10.1109/ADPRL.2013.6614987     Document Type: Conference Paper

References (29)

1. R. Bellman, Dynamic Programming. Princeton, NJ: Princeton Univ. Press, 1957.
2. P. J. Werbos, "ADP: The key direction for future research in intelligent control and understanding brain intelligence," IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, vol. 38, no. 4, pp. 898-900, 2008.
3. P. J. Werbos, "Intelligence in the brain: A theory of how it works and how to build it," Neural Networks, vol. 22, no. 3, pp. 200-212, 2009.
4. H. He, Self-Adaptive Systems for Machine Intelligence. Wiley, 2011.
5. P. J. Werbos, "Neural networks for control and system identification," in Proc. IEEE conf. decision control, pp. 260-265, 1989.
6. P. J. Werbos, Handbook of itelligent control, ch. Approximate dynamic programming for real-teim control and nerual modeling. New York: Van Nostrand Reinhold, 1992.
7. D. Prokhorov and D. Wunsch, "Adaptive critic designs," IEEE Transactions on Neural Networks, vol. 8, no. 5, pp. 997-1007, 1997.
8. J. Si and Y.-T. Wang, "Online learning control by association and reinforcement," Neural Networks, IEEE Transactions on, vol. 12, no. 2, pp. 264-276, 2001.
9. L. Yang, J. Si, K. S. Tsakalis, and A. A. Rodriguez, "Direct heuristic dynamic programming for nonlinear tracking conrol with filtered tracking error," IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, vol. 39, no. 6, pp. 1617-1622, 2009.
10. G. K. Venayagamoorthy, R. G. Harley, and D. C. Wunsch, "Comparison of heuristic dynamic programming and dual heuristic programming adaptive critics for neurocontrol of a turbogenerator," IEEE Transactions on Neural Networks, vol. 13, no. 3, pp. 764-773, 2002.
11. R. Enns and J. Si, "Helicopter trimming and tracking control using direct neural dynamic programming," IEEE Transactions on Neural Networks, vol. 14, no. 4, pp. 929-939, 2003.
12. R. Enns and J. Si, "Helicopter flight control reconfiguration for main rotor actuator failures," AIAA Journal of Guidance, Control, and Dynamics, vol. 26, no. 4, pp. 572-584, 2003.
13. R. Enns and J. Si, "Apache helicopter stabilization using neuro-dynamic programming," AIAA Journal of Guidance, Control, and Dynamics, vol. 25, no. 1, pp. 19-25, 2002.
14. H. He, Z. Ni, and J. Fu, "A three-network architecture for on-line learning and optimization based on adaptive dynamic programming," Neurocomputing, vol. 78, no. 1, pp. 3-13, 2012.
15. H. He, Z. Ni, and D. Zhao, Reinforcement Learning and Approximate Dynamic Programming for Feedback Control, ch. Learning and Optimization in Hierarchical Adaptive Critic Design, pp. 78-95. Wiley-IEEE Press, 2013.
16. H. He, Z. Ni, and D. Zhao, "Data-driven learning and control with multiple critic networks," in Intelligent Control and Automation (WCICA), 2012 10th World Congress on, pp. 523-527, july 2012.
17. A. Al-Tamimi, F. Lewis, and M. Abu-Khalaf, "Discrete-time nonlinear hjb solution using approximate dynamic programming: convergence proof," IEEE Trans. on Syst. Man, Cybern., Part B, vol. 38, no. 4, pp. 943-949, 2008.
18. H. Zhang, Q. Wei, and Y. Luo, "A novel infinte-time optimal tracking control scheme for a class of discrete-time nonlinear systems via the greedy hdp iteration algorithm," IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, vol. 38, no. 4, pp. 937-942, 2008.
19. J. Fu, H. He, and X. Zhou, "Adaptive learning and control for mimo system based on adaptive dynamic programming," IEEE Trans. Neural Networks, vol. 22, no. 7, pp. 1133-1148, 2011.
20. J. Fu, H. He, and Z. Ni, "Adaptive dynamic programming with balanced weights seeking strategy," in Adaptive Dynamic Programming And Reinforcement Learning (ADPRL), 2011 IEEE Symposium on, pp. 210-217, april 2011.
21. J. Fu, H. He, Q. Liu, and Z. Ni, "An adaptive dynamic programming approach for closely-coupled mimo system control," in The 8th International Symposium on Neural Networks (ISNN), vol. 6677, pp. 1-10, 2011.
22. Z. Ni, H. He, D. Zhao, and D. Prokhorov, "Reinforcement learning control based on multi-goal representation using hierarchical heuristic dynamic programming," in The 2012 International Joint Conference on Neural Networks (IJCNN), June 2012.
23. Z. Ni, H. He, D. V. Prokhorov, and J. Fu, "An online actor-critic learning approach with Levenberg-Marquardt algorithm," in The 2011 International Joint Conference on Neural Networks (IJCNN), pp. 2333-2340, IEEE, 2011.
24. P. He and S. Jagannathan, "Reinforcement learning neural-networkbased controller for nonlinear discrete-time systems with input contraints," IEEE Transactions on Systems Man and Cybernetics Part BCybernetics, vol. 37, no. 2, pp. 425-436, 2007.
25. B. Igelnik and Y. H. Pao, "Stochastic choice of basis functions in adaptive function approximation and the functional-link net," IEEE Transactions on Neural Networks, vol. 6, no. 6, pp. 1320-1329, 1995.
26. J. Slotine and W. Li, Applied Nonlinear Control. Prentice Hall, New Jersey, 1991.
27. H. Khalil, Nonlinear Systems (3rd edition). Prentice Hall, New Jersey, 2001.
28. [Online], http://www.youtube.com/watch?v=OeZEDBz6ki0&feature=youtu. be.
29. X. Fang, H. He, Z. Ni, and Y. Tang, "Learning and control in virtual reality for machine intelligence," in Intelligent Control and Information Processing (ICICIP), 2012 Third International Conference on, pp. 63-67, july 2012.