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Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming.

, , , and . Int. J. Control, 86 (9): 1554-1566 (2013)

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A neural-network-based iterative GDHP approach for solving a class of nonlinear optimal control problems with control constraints., , , , and . Neural Comput. Appl., 22 (2): 219-227 (2013)Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming., , , and . Int. J. Control, 86 (9): 1554-1566 (2013)Bounded robust control design for uncertain nonlinear systems using single-network adaptive dynamic programming., , and . Neurocomputing, (2017)Neural Network H ∞ Tracking Control of Nonlinear Systems Using GHJI Method., , and . ISNN (2), volume 7952 of Lecture Notes in Computer Science, page 186-195. Springer, (2013)The Braess Paradox in Dynamic Traffic., , , , , and . CoRR, (2022)Neural-network-based optimal tracking control scheme for a class of unknown discrete-time nonlinear systems using iterative ADP algorithm., and . Neurocomputing, (2014)Generalized Hamilton-Jacobi-Isaacs Formulation-Based Neural Network H ∞ Control for Constrained Input Nonlinear Systems., , and . ICONIP (1), volume 7663 of Lecture Notes in Computer Science, page 218-225. Springer, (2012)The Braess's Paradox in Dynamic Traffic., , , , , and . ITSC, page 1018-1023. IEEE, (2022)Temperature Control in Water-Gas Shift Reaction with Adaptive Dynamic Programming., , and . ISNN (2), volume 7368 of Lecture Notes in Computer Science, page 478-487. Springer, (2012)Neural network observer-based optimal control for unknown nonlinear systems with control constraints., and . IJCNN, page 1-7. IEEE, (2015)