Chen Wen-ChihChen Cheng-Liang2019-05-212019-05-21199503681653https://scholars.lib.ntu.edu.tw/handle/123456789/409714This 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.journal article2-s2.0-0029259876https://www.scopus.com/inward/record.uri?eid=2-s2.0-0029259876&partnerID=40&md5=c6f91f378e06f0150ce9e4c5a764b0a6