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Lookup NU author(s): Dr Jie ZhangORCiD
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Recurrent neural network (RNN) is used to model product quality of batch Processes from Process operational data. Due to model-plant mismatches and unmeasured disturbances, the calculated control policy based on the RNN model may not be optimal when applied to the actual Process. Model prediction errors from previous runs are used to improve RNN model predictions for the current run. It is proved that the modified model errors are reduced from run to run. Consequently control trajectory gradually approaches the optimal control policy. The proposed scheme is illustrated on a simulated batch reactor © Springer-Verlag 2004.
Author(s): Xiong Z, Zhang J, Wang X, Xu Y
Publication type: Book Chapter
Publication status: Published
Book Title: Advances in Neural Networks - ISNN 2004
Print publication date: 01/01/2004
Series Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Place Published: Berlin
Library holdings: Search Newcastle University Library for this item