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Recurrent neural networks and their variants have received huge success in many difficult tasks, such as handwriting recognition and generation, natural language processing, acoustic modeling of speech, and so on. As a kind of recurrent neural network architectures, the long short-term memory (LSTM) has attracted great attention. Most research works focus on its structures, training algorithms and...
In this paper, a new data-based self-learning control scheme is developed to solve infinite horizon optimal control problems for continuous-time nonlinear systems. The developed optimal control scheme can be implement without knowing the mathematical model of the system. According to the input-output data of the nonlinear systems, a recurrent neural network (RNN) is employed to reconstruct the dynamics...
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