|Title:||Nonlinear PI controller design: a neural network approach||Authors:||Chen Wen-Chih
|Issue Date:||1995||Journal Volume:||26||Journal Issue:||2||Start page/Pages:||67-76||Source:||Journal of the Chinese Institute of Chemical Engineers||Abstract:||
This article uses a hierarchical, multilayered neural network to provide parameters for a nonlinear PI controller in response to local operating conditions. The Generalized Delta Rule is adopted for use in training the connective weights of the network for subsequent on-line variation of the network-based PI controller parameters during control. Several numerical examples and one example of a highly nonlinear neutralization process are supplied to demonstrate the superior servo as well as regulatory control performance of the proposed neural net-based nonlinear PI control system.
|Appears in Collections:||化學工程學系|
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