双级神经网络的前馈解耦控制提出了具有时变，非线性，不确定性和多变量耦合发酵过程中。
A double-level neural network for feedforward decoupling control is proposed for the fermentation process characterized with time-variable, nonlinear, uncertain and multivariable coupling.
针对多模型控制方法中模型数目巨大，计算时间长等问题，提出了分层递阶结构多模型自适应前馈解耦控制器。
To solve such problem as too many models and long computing time, a hierarchical multiple model adaptive decoupling controller is designed.
在建立电流源型PWM变流器稳态数学模型的基础上，分析了系统的耦合关系，提出了一种基于小偏量线性化的前馈解耦控制方案。
On the basis of the stationary state mathematical model of a PWM current-source converter, the paper analyzes the coupling of a converter and presents a simple decoupling feedforward control method.
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