The normal internal model control can get over the time delay of industrial process, but it cannot achieve a satisfactory performance during great mismatch of internal model with object model.
常规内模控制器具有克服时滞的优点，但是当被控对象与模型严重失配情况下，常规内模控制器的控制往往难以达到满意的效果。
This paper proposes an internal model control system based on recurrent neural network, and considers jigger layer loose condition as research object.
该文提出一种基于对角递归神经网络的内模控制系统，并以跳汰生产过程床层松散状况为对象进行了研究。
In view of large delay and uncertainty of the main steam temperature object in a power plant, combining with internal model controller, a control system based on adaptive PSD has been designed.
针对火电厂主汽温对象大迟延、不确定性的特点，结合内模控制器设计了基于自适应PS D控制器的控制系统。
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