On the basis of a evolving clustering method (ECM), a new modeling approach of T-S type dynamic fuzzy inference model is proposed.
以一种进化聚类算法(ecm)为基础，提出了一种新的T - S型动态模糊推理模型的建模算法。
For the dynamic model of inverted pendulum system, adopted fuzzy control method, the T-S fuzzy controller based on the state feedback was designed.
针对倒立摆系统动态模型，采用模糊控制方法，设计基于状态反馈的T - S型模糊控制器。
In view of modeling problems of nonlinear and dynamic system, a self organizing fuzzy identification algorithm (SOFIA) is presented based on t s model in this paper.
针对复杂非线性动态系统的模糊建模问题，基于T - S模型提出一种自组织模糊辨识算法。
Moreover, T-S model is used to adjust the dynamic fuzzy rules by the latter neural network, which can improve the adaptability of the control system.
采用T - S模型，由后件网络动态调整模糊规则，提高控制系统的适应性。
The T-S fuzzy models of the velocity loop and position loop are constructed via the table's nonlinear dynamic model. Robust-optimal controller of velocity-loop is designed for velocity orientation.
通过转台的非线性动力学模型建立了转台速度环以及位置环的T - S模糊模型，设计了实现速率定位功能的速度环鲁棒最优控制器。
The T-S fuzzy models of the velocity loop and position loop are constructed via the table's nonlinear dynamic model. Robust-optimal controller of velocity-loop is designed for velocity orientation.
通过转台的非线性动力学模型建立了转台速度环以及位置环的T - S模糊模型，设计了实现速率定位功能的速度环鲁棒最优控制器。
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