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• W1570487003 abstract "This chapter develops a neuro-optimal control scheme for unknown nonlinear discrete-time systems with discount factor in the cost function. The iterative adaptive dynamic programming (ADP) algorithm using globalized dual heuristic programming (GDHP) technique is introduced to obtain the optimal controller with convergence analysis in terms of cost function and control law. A neural network is constructed first to identify the unknown nonlinear system. Finally, two simulation examples are provided to verify the effectiveness of the present optimal control approach. Simulation results show that the iterative ADP algorithm using GDHP technique can obtain better control performance than basic ADP schemes, for example, heuristic dynamic programming. Controlled Vocabulary Terms discrete time systems; dynamic programming; heuristic programming" @default.
• W1570487003 created "2016-06-24" @default.
• W1570487003 creator A5004057129 @default.
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• W1570487003 date "2012-12-17" @default.
• W1570487003 modified "2023-09-25" @default.
• W1570487003 title "Optimal Control of Unknown Nonlinear Discrete-Time Systems Using the Iterative Globalized Dual Heuristic Programming Algorithm" @default.
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• W1570487003 doi "https://doi.org/10.1002/9781118453988.ch3" @default.
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