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Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 29705


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10005569
Solutions to Probabilistic Constrained Optimal Control Problems Using Concentration Inequalities
Abstract:
Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.
Digital Object Identifier (DOI):

References:

[1] D. Q. Mayne, J. B. Rawlings, C. V. Rao and P. O. M. Scokaert, Constrained Model Predictive Control: Stability and Optimality, Automatica, Vol. 36, pp. 789-814, 2000.
[2] T. Hashimoto, Y. Yoshioka, T. Ohtsuka, Receding Horizon Control with Numerical Solution for Thermal Fluid Systems, Proceedings of SICE Annual Conference, pp. 1298-1303, 2012.
[3] T. Hashimoto, Y. Yoshioka, T. Ohtsuka, Receding Horizon Control with Numerical Solution for Spatiotemporal Dynamic Systems, Proceedings of IEEE Conference on Decision and Control, pp. 2920-2925, 2012.
[4] T. Hashimoto, Y. Yoshioka and T. Ohtsuka, Receding Horizon Control for Hot Strip Mill Cooling Systems, IEEE/ASME Transactions on Mechatronics, Vol. 18, No. 3, pp. 998-1005, 2013.
[5] T. Hashimoto, Y. Yoshioka and T. Ohtsuka, Receding Horizon Control With Numerical Solution for Nonlinear Parabolic Partial Differential Equations, IEEE Transactions on Automatic Control, Vol. 58, No. 3, pp. 725-730, 2013.
[6] T. Hashimoto, Y. Takiguchi and T. Ohtsuka, Receding Horizon Control for High-Dimensional Burgers’ f Equations with Boundary Control Inputs, Transactions of the Japan Society for Aeronautical and Space Sciences, Vol. 56, No.3, pp. 137-144, 2013.
[7] T. Hashimoto, Y. Takiguchi and T. Ohtsuka, Output Feedback Receding Horizon Control for Spatiotemporal Dynamic Systems, Proceedings of Asian Control Conference, 2013.
[8] R. Satoh, T. Hashimoto and T. Ohtsuka, Receding Horizon Control for Mass Transport Phenomena in Thermal Fluid Systems, Proceedings of Australian Control Conference, pp. 273-278, 2014.
[9] T. Hashimoto, Receding Horizon Control for a Class of Discrete-time Nonlinear Implicit Systems, Proceedings of IEEE Conference on Decision and Control, pp. 5089-5094, 2014.
[10] T. Hashimoto, Optimal Feedback Control Method Using Magnetic Force for Crystal Growth Dynamics, International Journal of Science and Engineering Investigations, Vol. 4, Issue 45, pp. 1-6, 2015.
[11] T. Hashimoto, R. Satoh and T. Ohtsuka, Receding Horizon Control for Spatiotemporal Dynamic Systems, Mechanical Engineering Journal, Vol. 3, No. 2, 15-00345, 2016.
[12] M. V. Kothare, V. Balakrishnan and M. Morari, Robust Constrained Model Predictive Control Using Linear Matrix Inequalities, Automatica, Vol. 32, pp. 1361-1379, 1996.
[13] P. Scokaert and D. Mayne, Min-max Feedback Model Predictive Control for Constrained Linear Systems, IEEE Trans. Automat. Contr., Vol. 43, pp. 1136-1142, 1998.
[14] A. Bemporad, F. Borrelli and M. Morari, Min-max Control of Constrained Uncertain Discrete-time Linear Systems, IEEE Trans. Automat. Contr., Vol. 48, pp. 1600-1606, 2003.
[15] T. Alamo, D. Pe˜na, D. Limon and E. Camacho, Constrained Min-max Predictive Control: Modifications of the Objective Function Leading to Polynomial Complexity, IEEE Trans. Automat. Contr., Vol. 50, pp. 710-714, 2005.
[16] D. Pe˜na, T. Alamo, A. Bemporad and E. Camacho, A Decomposition Algorithm for Feedback Min-max Model Predictive Control, IEEE Trans. Automat. Contr., Vol. 51, pp. 1688-1692, 2006.
[17] D. Bertsimas and D. B. Brown, Constrained Stochastic LQC: A Tractable Approach, IEEE Trans. Automat. Contr., Vol. 52, pp. 1826-1841, 2007.
[18] P. Hokayema, E. Cinquemani, D. Chatterjee, F Ramponid and J. Lygeros, Stochastic Receding Horizon Control with Output Feedback and Bounded Controls, Automatica, Vol. 48, pp. 77-88, 2012.
[19] P. Li, M. Wendt and G. Wozny, A Probabilistically Constrained Model Predictive Controller, Automatica, Vol. 38, pp. 1171-1176, 2002.
[20] J. Yan and R. R. Bitmead, Incorporating State Estimation into Model Predictive Control and its Application to Network Traffic Control, Automatica, Vol. 41, pp. 595-604, 2005.
[21] J. A. Primbs and C. H. Sung, Stochastic Receding Horizon Control of Constrained Linear Systems with State and Control Multiplicative Noise, IEEE Trans. Automat. Contr., Vol. 54, pp. 221-230, 2009.
[22] M. Cannon, B. Kouvaritakis and X. Wu, Probabilistic Constrained MPC for Multiplicative and Additive Stochastic Uncertainty, IEEE Trans. Automat. Contr., Vol. 54, pp. 1626-1632, 2009.
[23] E. Cinquemani, M. Agarwal, D. Chatterjee and J. Lygeros, Convexity and Convex Approximations of Discrete-time Stochastic Control Problems with Constraints, Automatica, Vol. 47, pp. 2082-2087, 2011.
[24] J. Matuˇsko and F. Borrelli, Scenario-Based Approach to Stochastic Linear Predictive Control, Proceedings of the 51st IEEE Conference on Decision and Control, pp. 5194-5199, 2012.
[25] T. Hashimoto, I. Yoshimoto, T. Ohtsuka, Probabilistic Constrained Model Predictive Control for Schr¨odinger Equation with Finite Approximation, Proceedings of SICE Annual Conference, pp. 1613-1618, 2012.
[26] T. Hashimoto, Probabilistic Constrained Model Predictive Control for Linear Discrete-time Systems with Additive Stochastic Disturbances, Proceedings of IEEE Conference on Decision and Control, pp. 6434-6439, 2013.
[27] T. Hashimoto, Computational Simulations on Stability of Model Predictive Control for Linear Discrete-time Stochastic Systems, International Journal of Computer, Electrical, Automation, Control and Information Engineering, Vol. 9, No. 8, pp. 1385-1390, 2015.
[28] T. Hashimoto, Conservativeness of Probabilistic Constrained Optimal Control Method for Unknown Probability Distribution, International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering, Vol. 9, No. 9, pp. 11-15, 2015.
[29] T. Hashimoto, A Method for Solving Optimal Control Problems subject to Probabilistic Affine State Constraints for Linear Discrete-time Uncertain Systems, International Journal of Mechanical and Production Engineering, Vol. 3, Issue 12, pp. 6-10, 2015.
[30] B. Øksendal, Stochastic Differential Equations: An Introduction with Applications, Springer, 6th edition, 2010.
[31] S. Boucheron, G. Lugosi and P. Massart Concentration Inequalities: A Nonasymptotic Thepry of Independence, Oxford University Press, 2013.
[32] J. Nocedal and S. J. Wright, Numerical Optimization, Springer Series in Operation Research and Financial Engineering, Springer, 2006.
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