Fixed Final Time Optimal Adaptive Control of Linear Discrete-Time Systems in Input-Output form

[1] F. L. Lewis and V. L. Syrmos, Optimal Control, 2nd edition. New York: Wiley, 1995.Search in Google Scholar

[2] D. Kirk, Optimal Control Theory: An Introduction, New Jersey, Prentice-Hall, 1970.Search in Google Scholar

[3] Z. Chen and S. Jagannathan, “Generalized Hamilton-Jacobi-Bellman formulation based neural network control of affine nonlinear discretetime systems”, IEEE Trans. Neural Networks, vol. 7, pp. 90-106, 2008.10.1109/TNN.2007.900227Search in Google Scholar

[4] S. J. Bradtke and B. E. Ydstie, Adaptive linear quadratic control using policy iteration, in Proc. Am Contr. Conf., Baltimore, pp. 3475-3479, 1994.Search in Google Scholar

[5] Z. Qiming, X. Hao and S. Jagannathan, “Finitehorizon optimal control design for uncertain linear discrete-time systems”, Proceedings of IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL), Singapore, 2013.Search in Google Scholar

[6] X. Hao, S. Jagannathan and F. L. Lewis, “Stochastic optimal control of unknown networked control systems in the presence of random delays and packet losses,” Automatica, vol. 48, pp. 1017-1030, 2012.Search in Google Scholar

[7] T. Dierks and S. Jagannathan, “Online optimal control of affine nonlinear discrete-time systems with unknown internal dynamics by using timebased policy update,” IEEE Trans. Neural Networks and Learning Systems, vol. 23, pp. 1118-1129, 2012.Search in Google Scholar

[8] R. Beard, “Improving the closed-loop performance of nonlinear systems,” Ph.D. dissertation, Rensselaer Polytechnic Institute, USA, 1995.Search in Google Scholar

[9] T. Cheng, F. L. Lewis, and M. Abu-Khalaf, “A neural network solution for fixed-final-time optimal control of nonlinear systems,” Automatica, vol. 43, pp. 482-490, 2007.10.1016/j.automatica.2006.09.021Search in Google Scholar

[10] A. Heydari and S. N. Balakrishnan, “Finitehorizon Control-Constrained Nonlinear Optimal Control Using Single Network Adaptive Critics,” IEEE Trans. Neural Networks and Learning Systems, vol. 24, pp. 145-157, 2013.10.1109/TNNLS.2012.2227339Search in Google Scholar

[11] P. J. Werbos, “A menu of designs for reinforcement learing over time,” J. Neural Network Contr., vol. 3, pp. 835-846, 1983.Search in Google Scholar

[12] J. Si, A. G. Barto, W. B. Powell and D. Wunsch, Handbook of Learning and Approximate Dynamic Programming. New York: Wiley, 200410.1109/9780470544785Search in Google Scholar

[13] A. Al-Tamimi and F. L. Lewis, ”Discrete-time nonlinear HJB solution using approximate dynamic programming: convergence proof,” IEEE Trans. Systems, Man and Cybernetics, Part B: Cybernetics, vol. 38, pp. 943-949, 2008.Search in Google Scholar

[14] H. Xu and S. Jagannathan, “Stochastic optimal controller design for uncertain nonlinear networked control system via neuro dynamic programming, IEEE Trans. Neural Netw. And Learning Syst, 24 (2013), pp. 471-484.Search in Google Scholar

[15] C. Watkins, “Learning from delayed rewards,” Ph.D. dissertation, Cambridge University, England, 1989.Search in Google Scholar

[16] W. Aangenent, D. Kostic, B. de Jager, R. van de Molengraft and M. Steinbuch, Data-based optimal control, in Proc. Amer. Control Conf., Portland, OR, 2005, pp. 1460-1465.Search in Google Scholar

[17] R. K. Lim, M. O. Phan, and R. W. Longman, “State-space system identification with identified Hankel matrix,” Dept. Mech. Aerosp. Eng., Princeton Univ., NJ, Tech. Rep. 3045, Sep, 1998.Search in Google Scholar

[18] M. O. Phan, R. K. Lim and R.W. Longman, “Unifying input-output and state-space perspectives of predictive control”, Dept. Mech. Aerosp. Eng., Princeton Univ., NJ, Tech. Rep. 3044, Sep, 1998Search in Google Scholar

[19] F. L. Lewis and K. G. Vamvoudakis, “Reinforcement learning for partial observable dynamic process: adaptive dynamic programming using measured output data”, Trans. On Systems, Man, and Cybernetics - Part B. Vo. 41, pp. 14-25, 2011.10.1109/TSMCB.2010.2043839Search in Google Scholar

[20] S. Jagannathan, Neural Network Control of Nonlinear Discrete-Time Systems, Boca Raton, FL: CRC Press, 2006.Search in Google Scholar

[21] M. Green and J. B. Moore, “Persistency of excitation in linear systems,” Syst. and Cont. Letter, vol. 7, pp. 351-360, 1986.10.1016/0167-6911(86)90052-6Search in Google Scholar

[22] K. S. Narendra and A. M. Annaswamy, Stable Adaptive Systems, New Jersey: Prentice-Hall, 1989.Search in Google Scholar

[23] F. L. Lewis, S. Jagannathan, and A. Yesildirek, Neural Network Control of Robot Manipulators and Nonlinear Systems, New York: Taylor & Francis, 1999.Search in Google Scholar

[24] H.K. Khalil, Nonlinear System, 3rd edition, Prentice-Hall, Upper Saddle River, NJ, 2002.Search in Google Scholar

[25] R. W. Brochett, R. S. Millman, and H. J. Sussmann, Differential geometric control theory, Birkhauser, USA, 1983. Search in Google Scholar