In this paper , to resolve the coupling phenomena between temperature and humidity in wood drying system , a bp neural network based pid controller is proposed and applied to wood drying system . the architecture and learning algorithm of the proposed controller is more simpler and the physical meanings of the input layer ' s neurons and output layer ' s neurons are explicit . based on predefined control rules and self - learning , the bp network changs the scaling integral and differential parameters , therefore is able to control the variants using classical pid control algorithms and at the same time , decoupling control is implemented as well during the control procedure
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