A novel generalized value iteration scheme for uncertain continuous-time linear systems

Proceedings of the IEEE Conference on Decision and Control

Volumn , Issue , 2010, Pages 4637-4642

  Lee, Jae Young ^a   Park, Jin Bae ^a   Choi, Yoon Ho ^b  

^a Yonsei University   (South Korea)

^b Kyonggi University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

CLOSED LOOP SYSTEMS; DYNAMICAL SYSTEMS; ITERATIVE METHODS; LEARNING SYSTEMS; LINEAR SYSTEMS; ONLINE SYSTEMS; REINFORCEMENT LEARNING;

CONTINUOUS-TIME LINEAR SYSTEMS; CONTINUOUSTIME; LINEAR QUADRATIC REGULATION PROBLEMS; MONOTONE CONVERGENCE; OPTIMAL SOLUTIONS; SYSTEM MATRICES; VALUE FUNCTIONS; VALUE ITERATION;

CONTINUOUS TIME SYSTEMS;

EID: 79953145872     PISSN: 07431546     EISSN: 25762370     Source Type: Conference Proceeding    
DOI: 10.1109/CDC.2010.5718015     Document Type: Conference Paper

References (15)

1. R. S. Sutton and A. G. Barto, Reinforcement Learning - An Introduction MIT Press, Cambridge, Massachussetts, 1998.
2. J. Si, A. G. Barto, W. B. Powell, and D. Wunsch, Handbook of learning and approximate dynamic programming, Wiley-IEEE Press, 2004.
3. D. V. Prokhorov and D. C. Wunsch II, "Adaptive critic designs," IEEE Trans. Neural Networks, vol. 8, no. 5, pp. 997-1007, 1997.
4. S. J. Bradtke and B. E. Ydstie, "Adaptive linear quadratic control using policy iteration," Proc. American Control Conference, Baltimore, Maryland, pp. 3475-3479, 1994.
5. A. Al-Tamimi , M. Abu-Khalaf, and F. L. Lewis, "Model-free Q-learning designs for discrete-time zero-sum games with application to H¥ control," Automatica, vol. 43, no. 3, pp. 473-481, 2007.
6. W. C. Wong and J. H. Lee, "A reinforcement learning-based scheme for adaptive optimal control of linear stochastic systems," Proc. American Control Conference, Seattle, WA, USA, pp. 57-62, 2008.
7. L. C. Baird III, "Reinforcement learning in continuous-time: advantage updating," Proc. IEEE World Congr. Computational Intelligence, IEEE International Conf. Neural Networks, Orlando, 1994, vol. 4, pp. 2448-2453.
8. K. Doya, "Reinforcement learning in continuous-time and space," Neural Computation 12, pp. 219-245, 2000.
9. P. Mehta and S. Meyn, "Q-learning and Pontryagins minimum principle," Proc. Decision and Control, pp. 3598-3605, Dec., 2009.
10. J. J. Murray, C. J. Cox, G. G. Lendaris, and R. saeks, "Adaptive Dynamic Programming," IEEE Trans. Systems, Mans and Cybernetics, vol. 32, no. 2, pp. 140-153, 2002.
11. D. Vrabie, O. Pastravanu, M. Abu-Khalaf, and F. L. Lewis, "Reinforcement learning and adaptive dynamic programming for feedback control," Automatica, vol. 45, no. 2, pp. 477-484, 2009.
12. D. Vrabie, M. Abu-Khalaf, F. L. Lewis, and Y. Wang, "Continuous-time ADP for linear systems with partially unknown dynamics," Proc. the IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning, pp. 247-253, 2007.
13. B. D. O. Anderson and J. B. Moore, Linear Optimal Control, Englewood Cliffs, NJ: Prentice Hall, 1971.
14. G. Strang, Linear Algebra and Its Applications, California: Thomson Higher Education, 2006.
15. ∞ control of systems with parameter uncertainties," International Journal of Control, vol. 63, no. 4, pp. 741-750, 1996.