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• W2569685483 abstract "In this chapter, we consider optimal control problems of continuous-time nonaffine nonlinear systems with completely unknown dynamics via adaptive dynamic programming (ADP) methods. First, we develop an ADP-based identifier–actor–critic architecture to obtain the approximate optimal control for continuous-time unknown nonaffine nonlinear systems. The identifier is constructed by a dynamic neural network, which transforms nonaffine nonlinear systems into a kind of affine nonlinear systems. After that, the actor–critic dual networks are employed to derive the optimal control for the newly formulated affine nonlinear systems. Second, we present an ADP-based observer–critic architecture to obtain the approximate optimal output regulation for unknown nonaffine nonlinear systems. The present observer is composed of a three-layer feedforward neural network, which aims to obtain the knowledge of system states. Meanwhile, a single critic neural network is employed for estimating the performance of the systems as well as for constructing the optimal control signal." @default.
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• W2569685483 date "2017-01-01" @default.
• W2569685483 modified "2023-09-26" @default.
• W2569685483 title "Optimal Control of Unknown Continuous-Time Nonaffine Nonlinear Systems" @default.
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• W2569685483 doi "https://doi.org/10.1007/978-3-319-50815-3_8" @default.
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