Iterative Adaptive Dynamic Programming by Qinglai Wei (.PDF)

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File Size: 12.1 MB

Iterative Adaptive Dynamic Programming for Self-Learning Optimal Control (Series on Deep Learning Neural Networks: Volume 2) by Qinglai Wei, Ruizhuo Song, Hongyang Li
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Overview: This unique book introduces the iterative adaptive dynamic programming theory from the control systems perspectives, with the most recent results of iterative adaptive dynamic programming methods. Advanced theoretical analysis and some practical applications of iterative adaptive dynamic programming are provided. Furthermore, the practical applications in residential energy systems are also highlighted, showing the good performance of the iterative adaptive dynamic programming methods. Adaptive dynamic programming (ADP) employs approximation structures, such as neural networks, to approximate the performance index function in dynamic programming, such that the performance index function satisfies the HJB equation. There are generally three modules in ADP, which are model, critic and action modules, respectively. Every module can be realized by neural networks. The useful reference text benefits professionals, researchers, academics, graduate and undergraduates students in control engineering.
Genre: Non-Fiction > Tech & Devices

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