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- W1480969069 abstract "This paper proposes the use of error back proragation (BP) neural network to efficiently control the pH in the clarifying process of sugar cane juice. In particular approximate dynamic programming (ADP) is implemented to solve this nonlinear control problem. The neural network model of the clarifying process of sugar cane juice and a neural network controller based on the idea of ADP to achieve optimal control are developed. The strategy and training procedures of dual heuristic programming (DHP) are discussed. The result is the “plant” has been effectively controlled using DHP.Keywordsapproximate dynamic programmingdual heuristic programmingoptimal controlclarifying process" @default.
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- W1480969069 date "2010-01-01" @default.
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- W1480969069 title "PH Optimal Control in the Clarifying Process of Sugar Cane Juice Based on DHP" @default.
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- W1480969069 doi "https://doi.org/10.1007/978-3-642-14922-1_38" @default.
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