本文使用一個逆傳遞類神經網路調諧比例積分控制器的參數值，經過適當的訓練之後，即可透過類神經網路為控制器參數與程序狀態之間建立一個極佳的函數關係，可以有效地處理非線性程序之控制問題。文中以三個困難程序及酸鹼中和程序之控制為例說明此一比例積分類神經控制器的優越控制性能。
This article uses a hierarchical, multilayered neural network to provide parameters fro 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 serve as well as regulatory control performance of the proposed neural net-based nonlinear PI control system.
關聯:
Journal of the Chinese Institute of Chemical Engineers 26:2 民84.03 頁67-79
