对处于扰动状态下的预分馏塔的仿真结果表明，该算法可以有效地解决一类多神经网络模型的在线参数辨识问题。
Simulation results of a disturbed pre-fractionator show that this algorithm can be used to solve on-line parameters-recognized problem of a kind of multi- neural networks model effectively.
本文研究一类非线性神经网络自适应控制系统，提出一种基于双误差——辨识误差和跟踪误差的新控制方案。
A class of nonlinear neural network adaptive control systems is studied and a new design concept based on double errors was proposed in this paper.
然后介绍了如何使用模糊聚类算法和等价的前馈神经网络从样本数据中辨识离散的TS模型。
Then we introduce how to identify the TS model from sample data using fuzzy clustering algorithm and equivalent feedforward neural network.
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