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This paper presents that FCP network model and improved T-S model used in the disquisition are universal approximator, with the latter proved.

本文指出文中用到的FCP网络模型和改进T-S模型为通用逼近器,同时给出后者的证明。

Methods The relationship of dynamic model′s input and output was analyzed and a basic structure of system identification model based on the principle of optimization in model reduction and the property of a function approximator to be composed of feed-forward networks was presented.

分析了控制系统动态模型的输入、输出关系,依据模型等效的最优化原理和神经网络任意逼近有限不连续函数的性质,提出神经网络辨识模型的基本结构。

Prove that this kind of fuzzy inference model is an universal approximator, and proposed one method identifying this fuzzy model from training data set.

提出了带概率因子的模糊推理模型,证明了该种模糊推理系统是一个通用逼近器,并给出了一种从训练数据集中辨识该模糊模型的方法。

The Universal approximator and the universal controller are introduced.

针对模糊控制系统提出通用逼近子与通用控制器概念。

The states of system and the faults in system are estimated simultaneously. The inputs of the fault approximator are the estimated states.

首先提出一种状态估计器设计方法;然后在进行状态估计的同时用RBF神经网络来逼近系统所发生的故障。

Finally a generalized fuzzy hyperbolic model is proposed, which is proven to be a universal approximator, and two identification algorithms are derived.

最后提出一种广义模糊双曲正切模型,并证明了此模型具有全局逼近性。

The common assumptions on the time-delays of the system are not required; only one fuzzy approximator is needed for compensating all the unknown functions. Thus, the structure of the controller is simplified.

该方法取消了对系统时滞常做的假设,仅采用一个模糊逼近器便使所有的未知函数得到补偿,简化了控制器的结构。

The control system consists of a feedback controller, and a feed-forward part that is implemented as a function approximator.

前馈控制器采用B样条网络来做函数逼近器。

RBF networks have several following advantages: being a best universal approximator, having rapid learning speed and a compact topological structure.

径向基函数网络被认为是通用的函数逼近子并具有快速的学习能力和紧致的拓扑结构等优点。

Combined Nussbaum gain with the backstepping techniques, a novel algorithm was proposed by employing fuzzy systems as approximator of those unknown nonlinearities in the system.

将ISS理论引入所研究系统,利用模糊系统逼近系统中的未知非线性;利用Nussbaum增益技术解决系统中的控制方向未知的高频控制增益,提出了一种基于反推设计方法的鲁棒自适应模糊控制算法。

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